{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CLR Callback"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from clr_callback import *\n",
    "from keras.optimizers import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test Set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from keras.models import Sequential, Model\n",
    "from keras.layers import Dense, Activation, Input"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "inp = Input(shape=(15,))                \n",
    "x = Dense(10, activation='relu')(inp)\n",
    "x = Dense(1, activation='sigmoid')(x)\n",
    "\n",
    "model = Model(inp, x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "X = np.random.rand(2000000,15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "Y = np.random.randint(0,2,size=2000000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Callback test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following tests callback functionality for each default Keras optimizer."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tests demonstrate expected cyclical behavior, as well as functionality of resetting the cycles and/or adjusting boundary values."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SGD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='triangular')\n",
    "\n",
    "model.compile(optimizer=SGD(0.1), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7f8f34af34e0>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f8f3069ca58>]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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aiCxNoD05LxhyQxorsjekMZ7FZSXcvsYGrU2l90puhDTG874Nboijfc+T2n+y\nm8GR8Zy7K28qiUSkDKrqhKqOqerXgb8CHkzgsw8BdSKyVkRKgA/j3Eoc7RngUffurbuAXlW9MNW6\nqvqWqtaq6hpVXYPT5XWrqnr+8PZC7xXeasuNkMZ4Av6lHA8PcKY7Iye2WW3f8U7GJjTndzDzigu5\nd2M1jU0W4jiZYChMWUkhd6+vynRTkmK6AYkLReSzIvJXIrLL3dl/GmgFfi7eB6vqGPBp4MdAE/Ad\nVT0qIo+LyOPuYs+6n9cC/C3wyenWnfVWekDkyC7XdzBwbRvsrOS9gqEw1eUlbFmZO4NNp9JQ7+NC\n7xBvt1mIY7SJCeemmVwOaYw13a0//wRcBPYDn8C5NiHAz6jqG4l8uKo+i1Msol/7atRzBT6V6LqT\nLLMmkXZ4QbCpg7XVud1vHrGysozNS50Qx09sX5fp5mSNkbEJ9h7r4AM3LsuJkMZ4dtb7KBAnieHG\nFYsy3Zys8VZbL+G+YU/0LkRM17W1TlV/UVX/BngEZzzH+xMtIiZ5+odG2X+yK6dCGuMJ+H0cOt1j\nIY5RDp7qpn94LGdv+41VuaCErasr7TbgGMFQmMICyemQxljTFZKrw1JVdRw4p6pDqW+SibXvuDO5\nkRcGLkUE/D4mFJ47ZoPWIoKhMPOKC9i2IfcGm04l4PdxrL3fQhyjBENhtq5ewpIcDmmMNV0huVlE\n+txHP3BT5LmIWKdnGgVDYSoXlORUSGM8N1y3CN9CC3GMcCY3CrO9LrdCGuOJdN/YFLyOd7ov0xzu\n91S3FkyftVWoqgvdR4WqFkU9X5jORuaz0fEJnj/WwQObc2Nyo0Q5g9Z8vHDCQhzhWkij13Ywa6oX\nUFdbbgcMrmszm3prxELuxMfmqVdyOKQxnkiI48snuzLdlIyLTG6000P95hENfh8HT/XQe9lCHIOh\ndjb5KlhVVZbppiSVFZIsF3RDGrfXeaffPOLu9VWUlxbZ0SpuSOPqJVTlYEhjPDapmePS5REOnb5I\ng997BwtWSLJYZHKj7XW5GdIYT2lRITs21tDY1JHXIY7nLl4mdKHPUzdTRNuyYjE1NqkZzx2LhDR6\nq1sLrJBktaYL/bRdyu2QxngCfh+d/cO8ee5SppuSMbke0hhPJMRxb3NHXoc4RkIab1ruvTE1icxH\n0h9191bkcVZE/k1EbDRZCl0NadzszR0MwH2batwQx/w9Wg02hVlfs4B1HhhsOpWA38dgHk9qNjQ6\nzr7jnTTwL9t5AAAgAElEQVT4vRHSGCuRM5IvAb+FE+O+AvhNnGl4vwV8LXVNM8Gmdm5Z6XQLeNXi\nshLuWFOZt4Wk98ooB1t7PNndEe2e9dWUlRTm7W3A+1u7uTwy7t2zzgSW+aCq/o2q9qtqn6o+hTPC\n/duAdwY2ZJnzl67wdluf53cw4BytnugY4HRX/oU47m3uYMwjkxtNZ15xIffW1dAY6sjLEMdgKMyC\nkkLu8UhIY6xECsllEfk5ESlwHz8HREa4599fRJpEjty8voOBa9uYj2clkZDGW1bm/uRG8TT4fbT3\nDfFWnk1qNjHhDDa9d2MNpUXeGWwaLZFC8hHgF4AOIOw+/6iIzMdJ6DUpEAyFWVe9gA213u03j7ga\n4phn3R4jYxPO5EabvdlvHuuBzbVuiGN+fc9H2nrp6PdWSGOsROYjaVXVn1bValWtcZ+3qOoVVX0p\nHY3MN31D3pjcaCZ2+X0cPt1DTx6FOB5odUIa8+V7rlxQwtY8vB4WDLV7LqQxViJ3bdWIyO+IyFMi\n8rXIIx2Ny1f7mt2QxjzZwYDT7ZFvIY7BUJj5xYVs8+Bg06nsysMQx2AozO1rlrC4zDshjbES6dr6\n38AioBH4YdTDpEgwFKZqQQm3rsqfexluXL6IpQvn5c1c7qrO5Ebb66o9M7lRIvLtetiZ7kGOhwc8\nf9NMIsOly1T1v6S8JQZwQxqbO3jw+qWeCmmMR0Ro8Nfyr6+2MTQ67vmd69HzfVzoHeIzgY2Zbkpa\nra5awEafE+L48W1rM92clIsUzIBHUwsiEjkj+YGIfCDlLTEAHGztod+jIY3xBPxLuTI6zk9avB/i\nuDsS0ujxHcxkGup9vHK6h0uXvX89LBgKezKkMVYiheTXcIrJFZuPJPUam5zJjbbX1WS6KWl317pK\nykuL8mLQmjO5USWVHprcKFH5EuJ4cXCEQ6d78uKgMJG7tipUtUBV59t8JKkVCWnctsFbkxslqrSo\nkB2bvB/ieLbnMk0X+jyZApuIm1cspjYPQhyfO9bBhObHWLApC4mIbHb/e+tkj/Q1MX+ELvTRdukK\nu/LgD28qgXonxPEND4c4Xhts6u0LsFMpKBB21vvY19zp6RDHYCiMb2EpN3owpDHWdBfbPwM8BvzZ\nJO8p8EBKWpTHIiGN93v4fvN47t9UezXE0at3rQVDYTbUlrO2ekGmm5Ixu/w+/uWVd3j5ZDf3b/Le\n3/vQ6DgvnOjkQ7csz4vBptNNtfuY+9/7J3lYEUmByM7TyyGN8SwqK+bOtd4dtNZ7eZSDp/Kj33w6\nd6+vckIcPfo97z/p7ZDGWAnNRyIi94jIz4vIo5FHqhuWb9ouXeHo+b68+cObTsDvo6VjgFMeDHHc\nezwyuVF+f8/ziiOTmoU9eT1stxvSeLdHQxpjJTKy/Z+ALwLbgNvdx9YUtyvveH1yo5mI/Bt48Wh1\ndyhMdXkpW1Z4P6QxnoZ6H+G+Yc+FOE5MOINNd2zybkhjrEQGJG4F/JqP2c9p1NgUZl3NAtZ7eHKj\nRK1YUkb9soUEQ2F++V7vzJ02PDbOvuZOfuqmZXnRbx7PA5uvXQ+72UPpx2+eu0Snx0MaYyXStfU2\nkJ+3l6RJPoY0xhPw+zh8xlshjgdaexjIo5DGeJYsKGHr6iWeux4WDIUpLBBP3kQwlUQKSTUQEpEf\ni8gzkUeqG5ZP9rohjV6PUZiJQL0T4rjHQ4MTg6F25hcX8r4N+RPSGE/A76M53M873d4JcQyGwtyx\nptLTIY2xEikknwN+Bvg8zq3AkYdJkkhI4y0evd11Nm5YvpBli+Z55mhVVWkMdXDvxvwKaYxnlzuW\nxitz0ZzuGuREx0DenXVOW0hEpBD4nKrui32kqX2eNzI2wd5jHeysr82rkMZ4RISGeh8vnuhiaDT3\nB6293dZHe99Q3g5CnMqqqjI2+So8k/qcTzObRpu2kKjqODAhIt4fmpkhB09FJjeyHUysgN/HldFx\nXjqR+yGOwVA7BYKnJzearQZ/LYdOX/REiOPuUJjNSytYWentkMZYiXRtDQBvicjfi8iTkUciHy4i\nD4pIs4i0iMgTk7wv7ue1iMiR6OiVqdYVkf/mLvuGiOwWkesSaUu2agw5IY3brN/8Pe5aV0WFR0Ic\nd+dxSGM8Af9Sxic05yc16xkc4XCehDTGSqSQfA/4PeAF4NWox7TcbrEvAw8BfuAREfHHLPYQUOc+\nHgO+ksC6/0NVb1LVLcAPgN9PYBuyUiSkcXtdfoY0xlNSVOCJEMezPZc51t6flzuYRNy0fJEnQhzz\nKaQxVtxxJKr69Vl+9h1Ai6q2AojIt4CHgVDUMg8DT7tjVA6IyGIRWQasmWpdVY2OsF+Ak/uVk46e\n7+N87xC/3pBfkxvNRMDv4wdHLvD62Uvctjo3b0YI2mDTaRUUCA1+H99/PbcnNQuG2lm6cF5ehDTG\nSmRke52IfFdEQiLSGnkk8NnLgbNRP59zX0tkmWnXFZE/FpGzwEeY4oxERB4TkcMicrizszOB5qZf\nJKTxgXrrN5/KfZtqKXIHreWqYChMXW05a/I4pDGegN/H5ZFx9p/sznRTZmVodJwXjnfR4K9FJP9u\nmkmka+sfcLqcxoD7gaeBb6SyUfGo6u+q6krgm8Cnp1jmKVXdqqpba2qyc5KoYCjMbauWUF2evyGN\n8SyaX8yd6ypz9q6e3sujvJKn/eYzcc/6KhaUFObsbcAvn+ziyuh43t40k0ghma+qewBR1TOq+jng\n3yWwXhuwMurnFe5riSyTyLrgFJKfTaAtWefcxcuELlhIYyIC9T5Odg7S2jmQ6abM2PPNFtKYiKuT\nmoVyM8QxGApTXlrEXesqM92UjEikkAyLSAFwQkQ+LSIfAhIJhDoE1InIWhEpAT4MxI6IfwZ41L17\n6y6gV1UvTLeuiNRFrf8wcCyBtmQdC2lMXEMkxDEHj1aDoTA1FaXcbCGNcTXU++joH+ZIjoU4OiGN\nHezYmD8hjbESnbO9DPjPwG3AR4GPxVtJVcdwup1+DDQB31HVoyLyuIg87i72LNAKtAB/C3xyunXd\ndb4gIm+LyBFgl9u+nNPY1MH6mgWss5DGuFYsKcPvhjjmkuGxcfY2d9BQX2shjQm4FuKYW92Yb+Rh\nSGOsRO7aOgQgIhOq+ksz+XBVfRanWES/9tWo5wp8KtF13ddzsisrWu8VJ6TxE9u9k2ybag1+H3/1\n3Am6B4apypFrSvtPdjOYR5MbzdXishJuX+OEOP7W+zdnujkJy8eQxliJ3LV1t4iEcLuQRORmEfnr\nlLfMw/Y2dzA2oQT8+fuHN1O7/G6IYw4NWguGwpSVFHLPehtsmqiAfynHwwOc6c6dSc2CoTB3rq1k\nUVlxppuSMYl0bX0JeD/QDaCqbwL3prJRXhcMhakuL2HLytwcF5EJ11+3kOtyKMRR1Znc6N66mpwd\nF5EJu9yzt1z5nk91DdKShyGNsRKaaldVz8a8lPspehkyMjbBvuZOdm72WUjjDIg4g9ZePNHJlZHs\n//N7q62XcF9+95vPxsrKMjYvrciZQhK5aaYhz6eASKSQnBWRewAVkWIR+U2cC+BmFg60RkIa8/sP\nbzYCfh9DoxP8pCX7QxyDobCFNM5SQ72PQ6d7uJgDk5oF8zSkMVYiheRxnAviy3HGcmzBvbvKzFxj\nU5j5xYVsq7N+85m6c60T4pgLR6vBUJitaypZYiGNMxZwr4dle4hjz+AIh8/0XO2Oy2dxC4mqdqnq\nR1TVp6q1qvpR4NE0tM1znMmNwmyvs8mNZqOkqID7Ntey51iY8SwetBYJabQdzOzcuHwRvoXZH+K4\npynshjTm52j2aAldI5nEZ5LaijwRCWlssB3MrDXU19I1MMIbZy9muilT2m2DTeekoMCZ1OyFE51Z\nPalZMBRm2aJ53LB8YaabknGzLSR2lXgWdrv95jut33zWIiGOu7P4aDUYamejr5zVVRbSOFuREMeX\nT2bn9bCh0XFePNFFQ70vL0MaY822kGRvv0IWC4bC3LZ6Sc4MqMtGi+YXc9e6qqzt9rh0eYRDpy/a\n2cgc3b2+ivLSIoKh7LxO8pOWSEijfc8wTSERkX4R6Zvk0Q/k9KyEmXC25zJNFtKYFAG/j9bOQU5m\nYYjjtZBG6zefi9KiQnZsrKGxKTtDHCMhjXfmaUhjrCkLiapWqOrCSR4Vqho3WsW8WyRw0HYwc3c1\nxDELz0qCoTC1FaXclIeTGyVbg7+Wzv5h3jx3KdNNeZerIY2b8jekMdZsu7bMDDU2hdlQW85am9xo\nzpYvns/112VfiOPw2Lgz2LTeZyGNSXD/pkiIY3Z9z6+fvUTXwLDdlRfFCkka9F4Z5WCrTW6UTA31\nPl595yJdA8OZbspVL7shjbaDSY7FZSXcsaYy6wpJMBSmqEC4L49DGmNZIUmDSEhjvscoJFPA70MV\nnmvKnouxkZDGu9dXZbopnhHw+zjRMcDpruwJcWxsCnPnukoWzc/fkMZYVkjSYHcoTHV5KbestMmN\nkuX66xayfPH8rLkNeGJC2dMUZsdGC2lMpkCWTWp2NaTRDgrfxQpJikX6zW1yo+QSERrqa3mpJTtC\nHC2kMTUiIY7ZcsAQmXTLBhW/mxWSFDvQ2sOAhTSmRMC/lKHRCV7KghBHm9wodQJ+H4dP99CTBSGO\nwVCY+mULWbEkv0MaY1khSbHGkBPS+L4NFtKYbHeuq6RiXlFWTM0aDIXZunqJhTSmQLaEOHYPDPPq\nGRtsOhkrJCl0dXKjjRbSmArFhQXct6mWPU0dGQ1xfKf7Ms3hftvBpMiNyxexdOG8jB8w7DnWwYRi\nd+VNwgpJCr3d1seF3iG7WyuFAn4f3YMjvP5O5kIcd7s7uF022DQlnEnNannheFdGQxyDoTDXLZrH\n9ddZSGMsKyQpFAy1OyGNVkhS5r5NNRQXZnbQWmNTmE2+ClZVWb95qgT8S7kyOp6xSc2ckMZOGvwW\n0jgZKyQptDsUZuvqSiqt3zxlFs7LbIijhTSmx13rKikvLcrYbcAvnehiaHTCvucpWCFJkcjkRvaH\nl3oBv4/WrsyEOD53LBLSaN9zKpUWFbJjUw2NTR0ZCXEMhsJUlBZx51obbDoZKyQpci2k0XYwqRa5\nBpWJs5JISOONFtKYcoF6H539w7yR5hDH8Qllz7EwOzbVUFJku8zJ2L9KigRDYepqy1ljIY0pd12G\nQhyHRsfZd9zpN7fBpqmXqRDHN85epGtgxA4Kp2GFJAV6L49y8JSFNKZTwO/jtXcu0tmfvhDH/Se7\nuTxikxuly6KyYu5cm/4Qx90W0hiXFZIUiExuZDEK6XM1xPFY+nYyu0NhFpQUco+FNKZNwO+jpWOA\nU2kMcWwMhblrXZWFNE7DCkkKBENhaipK2bLCQhrTxb/MCXFM19Hq1ZBGm9worQJpntSstXOAk52D\ndtYZhxWSJBseG2dvc4eFNKaZiBDw+3jxRBeXR8ZS/vuOtPXS0W8hjem2YkkZ9cvSdz0s8nt21lu3\n1nSskCTZfndyI9vBpF/A72N4bIKXTqR+0Fow1G4hjRkSqK/l8Jn0hDgGQ2H8FtIYV0oLiYg8KCLN\nItIiIk9M8r6IyJPu+0dE5NZ464rI/xCRY+7y/yYiWdV/1NjkTG50z3oLaUy3O9ZGQhxTf7QaDIW5\nfc0SFpfZYNN0C/iXMqGwJ8WDE7sGhnn1HRtsmoiUFRIRKQS+DDwE+IFHRMQfs9hDQJ37eAz4SgLr\nBoEbVPUm4Djw2VRtw0ypKo2hDu6ts8mNMqG4sID7N9VeHSSYKme6BzkeHiBg2VoZccPyhSxbNC/l\nBwzPNXWgamPBEpHKM5I7gBZVbVXVEeBbwMMxyzwMPK2OA8BiEVk23bqqultVI53gB4AVKdyGGXmr\nrZf2viG7WyuDIiGOr6UwxDGyA7MU2MxwJjVzroelMsRxdyjMcneMkpleKgvJcuBs1M/n3NcSWSaR\ndQE+Dvxosl8uIo+JyGEROdzZ2TnDps9OMBSmQOCBzdZvninpCHEMhsJsXlrBykrrN8+UgN/HldHx\nlF0PuzIyzkstzsymFtIYX85ebBeR3wXGgG9O9r6qPqWqW1V1a01NTVraFAyF2brGQhozqSIqxFE1\n+d1bFwdHOHTaBptm2l3rqqhIYYjjSy2RkEbrvkxEKgtJG7Ay6ucV7muJLDPtuiLyi8BPAR/RVOwt\nZiES0mjdHZm3y+/jVNcgJzuTP2jtOXdyI5tjJrNKigpSGuIYDLVTUVrEHWsrk/7ZXpTKQnIIqBOR\ntSJSAnwYeCZmmWeAR927t+4CelX1wnTrisiDwG8DH1TVyyls/4xEulLsSDXzIteoUtG9FQyF8S20\nkMZsEPD76BoY5vWzyQ1xHJ9Q9jR1cN/mWgtpTFDK/pXcC+KfBn4MNAHfUdWjIvK4iDzuLvYs0Aq0\nAH8LfHK6dd11/gqoAIIi8oaIfDVV2zATwVCYjb5yVldZSGOmLVs0nxuWL0z61KxDo+O8cKKThnoL\nacwG922qpSgFIY6vv3OR7kELaZyJolR+uKo+i1Msol/7atRzBT6V6Lru6xuS3Mw5u3R5hFdO9/D4\njnWZbopxBeqX8qU9x+nsH6amojQpn/nyyS4Lacwii+YXc+e6SoKhdp54aHPSPjcYClNcKNy3KT3X\nVr3AztuS4GpIo/WbZ41IiGMyB60FQx2UlxZxt4U0Zo1AvY+TnYO0JnFSs2CTE9K4cJ6FNCbKCkkS\nRCY3utlCGrNG/bKKpIY4TkwojU1hdmy0kMZsErkelqy7t052DtBqIY0zZoVkjobHxtnX3MlO6zfP\nKpEQx5dakhPi+Oa5S3T2D9PgtzFC2WTFkjL8SQxxvBbSaIVkJqyQzNHLbkij3fabfXa5IY4vJmHQ\nWjAUtpDGLNXg9/HqmYt0D8x9UrNgKMz11zlTEpjEWSGZo8aQE9Jo/ebZ5/a1lSxMUohjMBTmjjWV\nFtKYhXb5fU6I47GOOX1OZ/8wr1lI46xYIZmD6H5zC2nMPsWFBdy/ee4hjqe7BjnRMWA7mCx1/XUL\nuS4JIY7PHQtbSOMsWSGZg7faegn3DdvdWlks4PfRMzjCq2dmH+Jog02zm4jQ4Pfx4olOrozMPsQx\nGOpg+eL5+JdZSONMWSGZg0i/uYU0Zq8dGyMhjrMfnBhsspDGbBfw+xganeClltldD4uENAb8Pgtp\nnAUrJHMQDIXZunoJSyykMWtVzCvm7vXVsw5x7Bkc4fDpHruZIsvdudYNcZxl99aLJzrdkEb7nmfD\nCsksvdN9meZwv/3h5YCA38fp7sucnMWgtashjfY9Z7WSogLu21zLnmPhWV0PC4bCVMyzkMbZskIy\nS8GmyORGFjOd7Rrqna7H3bM4Wg2G2lm6cJ6FNOaAhvpaugZGeOPszK6HjU8ozx3r4P5NtRQX2i5x\nNuxfbZaCoXY2+SpYVWX95tlu2aL53Lh80Yzv6hkaHeeF4100+G1yo1wQCXGc6QHDaxbSOGdWSGbh\n0uURDp2+aKOcc0jA7+ONs5fo6B9KeJ2ftHRxZXTcJjfKEYvmX5vUbCYspHHurJDMQmRcgu1gcse1\nEMfEB601NoUpLy3irnXWb54rAn4frZ2DM7oe1hhyQhorLKRx1qyQzEIkpPEm6zfPGZuXVrBiSeIh\njs5g0w52bLKQxlxyNcQxwe+5pWOA1q5BuytvjqyQzNDQ6Dj7jnfS4LeQxlwy0xDHN9yQxoANNs0p\nyxfP5/rrEg9xtJDG5LBCMkP7T3bb5EY5KuD3MTI2wQvH4w9as5DG3NVQ7+PVdy7SlUCIYzDUzg3L\nF3KdhTTOiRWSGQo2hVlQUsg9FtKYc25fk3iIYzAU5s61lSwqs37zXBO5HvZcnOthnf3OfO+BervW\nOVdWSGZgYkJpDIWt3zxHFRcW8MDmWp47FmZsfGLK5U51DdJiIY05KxIDH+824D1NFtKYLFZIZuBI\nWy8d/RbSmMsC/qVcvDw6bYhjo4U05jQRoaG+lpdapg9xbGwKs3zxfOqXVaSxdd5khWQGgqF2C2nM\ncTs21VBSWDBt91YwFKZ+2UJWLLHBprkq4F/K0OgEL57onPT9yyNjvHiiy0Iak8QKyQwEQ2FuX7PE\nJjfKYeWlRdy9vopg0+Qhjj2DIxw+00Og3g4Wctmd6yqpmFc05VzuL57oYnjMQhqTxQpJgs50D3I8\nPGCDED0g4PdxpvsyLR3vHbS2pynMhGLfc44rLizg/k217GmafFKzYCjMQgtpTBorJAmKdIXYwKXc\nF7nGNdnF2GAozLJF87hhuU1ulOsa/D66B0d4/Z13Xw+7GtK42UIak8X+FRMUDNnkRl6xdNE8blrx\n3hDHodFxXjzRRUO99Zt7wX2bIpOavft7fvXMRXospDGprJAk4OLgCIdO99jdWh4SqHdDHPuuhThe\nC2m079kLFs6bPMSxsckJadyx0UIak8UKSQIikxvZDsY7Ate7mUxRg9aCoTAVpUXctc4Gm3pFwO+j\n1R0XBKCqBENh7l5fbSGNSWSFJAHBUBjfwlKb3MhDNvkqWFk5/+pdPdEhjSVF9r+FV0R6ESLf88nO\nAU51DdpBYZLZ/zFxDI2O88KJThrqLaTRS0SEQP1SXmrpYnB4jNfPXqJrYNh2MB5z3eL53LD8Wohj\n5AaLBru9O6mskMRhIY3eFQlxfPFEJ8FQmKIC4T4LafSchnofr71zkc7+YYKhMDcuX8SyRRbSmExW\nSOLYHQpfHcRmvOX2NUtYNL+Y3aEwwVA7d66rZNF86zf3mkiI47cPvcMbZy/ZQWEKpLSQiMiDItIs\nIi0i8sQk74uIPOm+f0REbo23roj8BxE5KiITIrI1le13+s3D7NhoIY1eVOSGOH7vtTZOdg7a3CMe\n5V/mhDh+cfdxC2lMkZQVEhEpBL4MPAT4gUdExB+z2ENAnft4DPhKAuu+DfxfwAupanvEm+7kRjY3\nu3dF71QabAfjSZFJzQCqy0vYvNRCGpMtlWckdwAtqtqqqiPAt4CHY5Z5GHhaHQeAxSKybLp1VbVJ\nVZtT2O6rbHIj77s3aiyBhTR610734vqG2nIbbJoCRSn87OXA2aifzwF3JrDM8gTXnZaIPIZzlsOq\nVatmsupVN61YzOM71llIo4eVlxbxxx+6wYqIx929ror/tGMdH7ljdaab4kmpLCQZpapPAU8BbN26\n9b2pbQl48IalPHiDhfd53UfutJ2L1xUVFvDZh+oz3QzPSmUhaQNWRv28wn0tkWWKE1jXGGNMFkjl\nNZJDQJ2IrBWREuDDwDMxyzwDPOrevXUX0KuqFxJc1xhjTBZI2RmJqo6JyKeBHwOFwNdU9aiIPO6+\n/1XgWeADQAtwGfil6dYFEJEPAX8J1AA/FJE3VPX9qdoOY4wx05PJZonzmq1bt+rhw4cz3QxjjMkp\nIvKqqsYdr2cj240xxsyJFRJjjDFzYoXEGGPMnFghMcYYMyd5cbFdRDqBM7NcvRroSmJzcoFtc36w\nbc4Pc9nm1aoad07ivCgkcyEihxO5a8FLbJvzg21zfkjHNlvXljHGmDmxQmKMMWZOrJDE91SmG5AB\nts35wbY5P6R8m+0aiTHGmDmxMxJjjDFzYoXEGGPMnFghmYaIPCgizSLSIiJPZLo9syUiK0XkeREJ\nichREfk19/VKEQmKyAn3v0ui1vmsu93NIvL+qNdvE5G33PeelCyft1RECkXkdRH5gfuzp7dZRBaL\nyHdF5JiINInI3Xmwzb/h/l2/LSL/IiLzvLbNIvI1EekQkbejXkvaNopIqYh82339oIismVEDVdUe\nkzxw4utPAuuAEuBNwJ/pds1yW5YBt7rPK4DjgB/4U+AJ9/UngD9xn/vd7S0F1rr/DoXue68AdwEC\n/Ah4KNPbF2fbPwP8M/AD92dPbzPwdeAT7vMSYLGXtxlnWu5TwHz35+8Av+i1bQbuBW4F3o56LWnb\nCHwS+Kr7/MPAt2fUvkz/A2XrA7gb+HHUz58FPpvpdiVp2/43EACagWXua8uA5sm2FWdemLvdZY5F\nvf4I8DeZ3p5ptnMFsAd4IKqQeHabgUXuTlViXvfyNi8HzgKVOPMr/QDY5cVtBtbEFJKkbWNkGfd5\nEc5IeEm0bda1NbXIH2jEOfe1nOaest4CHAR86sxICdAO+NznU237cvd57OvZ6kvAbwMTUa95eZvX\nAp3AP7jdeX8nIgvw8DarahvwReAd4ALOLKu78fA2R0nmNl5dR1XHgF6gKtGGWCHJIyJSDvwr8Ouq\n2hf9njqHIp65F1xEfgroUNVXp1rGa9uMcyR5K/AVVb0FGMTp8rjKa9vsXhd4GKeIXgcsEJGPRi/j\ntW2eTKa30QrJ1NqAlVE/r3Bfy0kiUoxTRL6pqt9zXw6LyDL3/WVAh/v6VNve5j6PfT0bvQ/4oIic\nBr4FPCAi38Db23wOOKeqB92fv4tTWLy8zQ3AKVXtVNVR4HvAPXh7myOSuY1X1xGRIpxu0u5EG2KF\nZGqHgDoRWSsiJTgXoJ7JcJtmxb0z4++BJlX986i3ngE+5j7/GM61k8jrH3bv5FgL1AGvuKfRfSJy\nl/uZj0atk1VU9bOqukJV1+B8d8+p6kfx9ja3A2dFZJP70k4ghIe3GadL6y4RKXPbuhNowtvbHJHM\nbYz+rH+P8/9L4mc4mb6AlM0P4AM4dzidBH430+2Zw3ZswzntPQK84T4+gNMHugc4ATQClVHr/K67\n3c1E3b0CbAXedt/7K2ZwQS6D238f1y62e3qbgS3AYfe7/j6wJA+2+Q+BY257/wnnbiVPbTPwLzjX\ngEZxzjz/72RuIzAP+F9AC86dXetm0j6LSDHGGDMn1rVljDFmTqyQGGOMmRMrJMYYY+bECokxxpg5\nsUJijDFmTqyQGE8QkSoRecN9tItIW9TPJQl+xj9EjcGYaplPichHktTml0Rki4gUSJLTpUXk4yKy\nNOrnuNtmzGzZ7b/Gc0Tkc8CAqn4x5nXB+ZufmHTFNBORl4BP49zX36Wqi2e4fqGqjk/32ar6xtxb\naooXh0MAAAMaSURBVMz07IzEeJqIbBBnHpZvAkeBZSLylIgcFmcOi9+PWjZyhlAkIpdE5Asi8qaI\n7BeRWneZPxKRX49a/gsi8oo778M97usLRORf3d/7Xfd3bZmmmV8AKtyzp6fdz/iY+7lviMhfu2ct\nkXZ9SUSOAHeIyB+KyCFx5uL4qjj+I87AxG9Hzsgi2+Z+9kfFmZPibRH5vPvadNv8YXfZN0Xk+SR/\nRcYDrJCYfLAZ+AtV9auTFvuEqm4FbgYCIuKfZJ1FwD5VvRnYD3x8is8WVb0D+C0gUpR+FWhXVT/w\n33DSlqfzBNCvqltU9VERuQH4EHCPqm7BCWP8cFS7XlDVm1R1P/A/VfV24Eb3vQdV9ds46QX/0f3M\nkauNFVkB/BFwv9uu94kTcDndNv8BsNN9/UNxtsXkISskJh+cVNXDUT8/IiKvAa8B9TgTAcW6oqo/\ncp+/ijMXxGS+N8ky23CCIlHVN3HOhGaiAbgdOCwibwA7gPXueyPAv0Utu1NEXsGZyGgHcH2cz74T\nJ0epS52Qw3/GmTQJpt7mnwBPi8gnsH2GmURRphtgTBoMRp6ISB3wa8AdqnpJnETgeZOsMxL1fJyp\n/18ZTmCZmRLga6r6e+960UllvaLuhU0RKcPJS7pVVdtE5I+YfFsSNdU2/zJOAfop4DURuUVVL87h\n9xiPsaMLk28WAv04KajLgPfHWX42fgL8HICI3MjkZzxXqTORUKRQgBPA93MiUu2+XiUiqyZZdT7O\npF1dIlIB/GzUe/040yrHOgjc735mpMtsX5ztWaeqB4DfAy6S/RM+mTSzMxKTb17DiVY/BpzB2ekn\n21/idAWF3N8Vwplxbjp/DxwRkcPudZI/BBpFpAAn8fVx4Hz0CqraLSJfdz//Ak6RiPgH4O9E5Apw\nR9Q650Tk94C9OGc+/5+q/jCqiE3mL8SJIxdgt6q+HWdbTJ6x23+NSTJ3p1ykqkNuV9puoC5y5mGM\n19gZiTHJVw7scQuKAP/JiojxMjsjMcYYMyd2sd0YY8ycWCExxhgzJ1ZIjDHGzIkVEmOMMXNihcQY\nY8yc/B/1/NfgqtzdNQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8f3069c9e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xlabel('Training Iterations')\n",
    "plt.ylabel('Learning Rate')\n",
    "plt.title(\"CLR - 'triangular' Policy\")\n",
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='triangular2')\n",
    "\n",
    "model.compile(optimizer=SGD(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7f8f3bbf4ef0>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=20, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular._reset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7f8f3bbff908>"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular],verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f8f3bbfff28>]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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FgDrzb8GwSgVdH90CYiar3YEVCRiZv8FATcnj0mi8RqnlUSzamwJMpdKMTkyz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\nzMxKcUdiZmaluCMxM7NS/g9XhkjHYliIvQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8f3bbff550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xlabel('Training Iterations')\n",
    "plt.ylabel('Learning Rate')\n",
    "plt.title(\"'triangular2' Policy Reset at 20000 Iterations\")\n",
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='exp_range', gamma=0.99994)\n",
    "\n",
    "model.compile(optimizer=SGD(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fbf6e96b9e8>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=20, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fbf6dd3e550>]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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S1ijL1eR7GJleYHxmMVrDiotAQHHaSLSbdhZnAejlLU1zEB1IYqxlIFi2u5mlLbME+KrD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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fbf6e6438d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xlabel('Training Iterations')\n",
    "plt.ylabel('Learning Rate')\n",
    "plt.title(\"CLR - 'exp_range' Policy\")\n",
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular._reset(new_base_lr=0.003, new_max_lr=0.009)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fb1b3e44208>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fb1b37e02e8>]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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HnJocrI5+WbRqNrrYO4Xf5+HAJmVwnMaKINQAvTHP+4xjVsZsOFdEngf6lVKX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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb1b3e24b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr = lambda x: 0.5*(1+np.sin(x*np.pi/2.))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(scale_fn=clr, scale_mode='cycle')\n",
    "\n",
    "model.compile(optimizer=SGD(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fbf6e142908>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=40, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fbf6ddd60b8>]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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mBRstTrixu2hWQt7iF250pJtTLQg2WsaG3YgkzIjk3cDvYmTcdwK/g1mG9xPA\nh5MrWvqZLbY+FAaXe94tzC00J9hoscc4F2b6mWtBsNHiXJjhDMkvqerfquopVT3pybM/Q1U/CYwl\nXL5UY1wezUuElxuYdX7zdQtmRNJ8PbsOQ/cwW54r1Fo9r/c6DmNIFkTk+SLS572eD9gZ7uva+duq\ny2PTUD+bBvtdT7ULOF0ygo0t+c6dIekaWp0TBqZjuN6FG8MYkhcALwKOAT/23r9QRDZhFHrXLXML\nzeedW8aGB52gXxfQyqx2S2XWs6vntNPqnDDw1fM67jCEWY8kp6rPVtUJVZ303h9U1dOq+s12FDKt\ntCLYaEnSr/qRb93DLYcKiZw7jagq7/ryD8nl52M/d6sp3pBsmvfZpWX+5PN3rasgb6FY4o8/dxdn\nFuPv+beqXuA/Jol6vnemyDu/dDcrK+l2/jRUJxORSeDlwB7//qr60uSKlX5aFWy0JOVXLS2t8Ef/\nehcA977tmbGfP40cOr7Ae776I75454P8228+KdZzVwQbm+8wWOHGJOr53+54kA/+5z0slJb5k+c+\nPPbzp5F3feWHXP/tQ1x4/hZ++eKdsZ7bCjZuaUKw0ZJkLOxV//A97nzgJM951A6mJkdiP39chPnV\n/h/wn8BXgPXrBAzQqmCjJSnhxvvWoRjkPceLAMzMx/8gz0ZwbSUp3GjnLayn1OKT3jN3IgFFCLtk\ntkh4wUZLksKNM/NnAbj3eLHrDcmwqr4x8ZJ0GYUWJyNaxocHE7nxsj73jqq29GB0G9lj5pqTuNS5\nCC4PMFlASdTzPTPGeBbPrh9DMu9d66Hj8XeWosU7k0/zzuWLPOUnEzt9ZMIE2z8nIpclXpIuo9VZ\n7ZaxzBAnzyzFLtyYyxfL7x88uT6Wj8l5jeqJ04ssx+xLblWw0TI2PJSIgoG95iTiQmnF3tvZBK55\ntlhqubNghRvjruflFS2PPLO+5zqNhDEkr8MYk9PerPZTvnVK1i2V4FxrDYx1lcQt3Oh/yLLH0n3z\nxYUdkZSWVjhSOB3ruVsVbLSMZ5IRbrTXfN/sAmeXet/jXFpa4ZDnts0l0KgWFlpPnBno72PrpviF\nGx+YO83ZJdPRTMJ4xkmYrK3NqtqnqptUdYv3/7pf1Mr2PqLESCD+4XAuP8/0ZAZI/80XF7mZInsn\nvGueifeaWxXysyQRIzmzuMwDJ04zNZlhRZNx9aSN+2YXWF5R9k5kODJ3OvY5G1HrOQmZFPv87p3I\nJGI846SWXlYGAAAgAElEQVSmIRGRn/T+Xlzt1b4ippOorq0khBtVlWy+yOOmtrF5w8C6cHucPLNI\n/tRZnnbhOUClpx4XRlq89QYmCeHGe2aKqFK+5vVQz/Yay9ccY4fBCja2+ixDMsKN1ng87cJzmJk/\nm0iSQVzUG5G83vv7jiqvtydcrtRTKBrBxo2DrS0kaV1icfZiZoslTpxeZHpyhKntI6n3q8aBfdge\nfcEYY8OD5dhBXLSy2JGfJIQbbU/1aT/lGc91UM9ZX6MK8bq3rGBjlHpOQko+m59n66ZB9l9glKjS\n3GGot9Tu1d7fJ7evON1DHENhc574bj7biE5PZpieyPDt3PHYzp1W7MM1PTnC1ORI/COSYomfPLd1\nT64/o2driwH7ILl8ERF42PlbOXfLxtivOY3k8vNMbt7Aw3dsRSRet205AzOiC/POB+INHefyRfMs\nbx8p//+o3emUNwwVQRSRJ4jIr4vIVfaVdMHSTquCjRbbwMTZi7ENyvTkCNPbRzh64kzPp4dm8/P0\n9wm7x4eZmsjEPiIxHYbW69l2NuKUz8jm5zl/6yY2DfUzvT1DNuZrTiPZ/DxTExk2DvazY3RTrCOS\nSrwzWj0nMSKZmhxh9/gwA32S6phnmPVIPopxZT0ReIz32p9wuVJPq4KNFivcOBfziGRooI/zRzeV\nA+739Hgjk8sX2T0+zNBAH9PbR8ifOsvJM/H4kqMINlpsLzfWes4XmfLqd3pyhNyx+Z5fPCs3U5mQ\nNz05EmuMJIpgo2VseIizS/EJN546s8ixU2eZmsww2N/H7m3DqQ64h5mQuB+4UHv9Tm2SuYUSu8eH\nI50jbuHGnNdr6++T8kOXzc/z0zu2xvYdacMO/wGmvMytXL7IRbtGI587imCjJW7hRlUll5/neft3\nAeaaT51dIn/qLNu3bIzlO9LGbLHE3MJipZ4nM9x872xsE26jCDZa/MKNO4Y2RS6TNRrT3nM8NTHS\n3SMS4A7g3KQL0m1EHZFA/MKNWV9P9YJtw/RJbwdil1eUe3zSERVfcjwPXBTBRkvcgn4/PnmWYmm5\n3Kjaa+7les764mD270JpObYJt1EEGy1x17MdcVXqOcOh4wuxT2COizCGZAK4S0S+KCI32FfSBUsz\ni55gY5QYCcQr3FhaWuG+2YXyw7ZhoJ/d48Op7sVE5UjhNKWllfLDFrcv2Qo2RukwxC3cmKvSqEJv\nzxkKXrPtLMU14TaKYKMlbuHGXL7oxf48QzIxQml5hftjnnAbF2F+ubckXYhuYy7iZETLWIzCjffN\nFlle0fJDBiSSxZQmbONpRySD/X3sHo/PlzxbHpG03mEQkVhHnsFrPnfLRoaH+nvakGTzJva3Y8y4\njKxByc3M88R9E5HPH0Ww0RJ38kw2P1+O/YEZkYC55j0TmXqHdoS6hkRE+oG3uBTg1czF4PIwx8cn\n6GddG1MTFYXQ6ckM3zo4w8qK0tfXe+KN5UZ1ImA8YxuRRHd5QPz1nBnq55wtGwDo65OumPkchVx+\nnj3bhun37uHtmzcwsmEgtmuOOhkRKp2N2Fxb+eLq+3qikgKcRvHGuq4tVV0GVkSkd6O1LRB1Vrsl\nTuFG+1D5RyTTkyOcXVrhyFw6h8NRyeaLjA4PrhoZTk9muPf4QizijXYU0apgo2VseKjsJouKTQn1\n956nYzSeaSSbL5ZHIWBGeVOTmfg6DBHVC6Ai3Dgbw+z25RUlN1Msx7/AtBVjw4OprecwMZJ54H9E\n5O9E5L32FebkInKJiNwtIgdF5Noqn4t3voMicrtfeqXWsSLyVm/fW0XkSyJyfpiyxElUwUZLnMKN\n2fw82zdvYPPGSpmmetx/brPUgo1qXOKNUQUbLXHGwvypv5bpyZFE9KfSgI39Vbvm2EYkEQQbLVa4\nMY407wfmTOxvamLtNac1qSLME/Jp4A+AbwC3+F518dxi7wMuBS4ErhSRCwO7XQrs815XA+8Pcexf\nquojVPUi4HPAm0NcQ6xEFWy0xCncaMQaVy98UxFvTOfNF5XcTHHNNU/FKFg5G1G9wBKXcOPpkhFr\nrHbNqr05Z8iKNa65Zk+8caEUfcLtbDGeeo5LuLGcpbZ9bT2nVSYljPrv31d7hTj3Y4GD3prvJeAT\nwOWBfS4HrlfDTcCoiJxX71hV9esQZIC2z2+Jy7U1HlOAzoo1Bntt45khRocHU3vzRcGKNQZXjYsz\ni2kuBpcHxCfcaMUaq/XOIV4hw7QQTC6w2EY2qvFU1UiLWvkZG45HSr4S71xbzzPzpVSKN4aZ2b5P\nRP5ZRO4SkZx9hTj3DuCw7//7vW1h9ql7rIj8iYgcBl5AjRGJiFwtIgdE5EA+nw9R3PBEFWy0WNdY\nVAVgv1ijHxHpWf95ZcLW6oet4kuO3jufLZYiTVIrlykm4cbK3ILV9bx3ImP0p3pw/ZlqsT///1Hd\nW1awMY4RiVl7Jnojn8vPr4n9QcWYprFjGMa19RGMy2kJeDJwPfCxJAvVCFX9PVXdBXwceHWNfT6g\nqvtVdf/k5GSs3z+7EH0yIsSXe56t8bCB6dX0omvLpjVXW8d6anIkloetUCxFks2wjMc0WS17zIg1\n7g30VDcN9XP+1k092WHIemKNWzaujmHs2ZaJRbwxDnkUy1hMLsxsldgfpNtVHcaQbFLVrwKiqodU\n9S3AM0McdwTY5ft/p7ctzD5hjgVjSH4lRFliZW5hMXKgHeLLPQ9O2PITt/5UWsjNVMQag0xPxmM8\nTYchxnqO2MjkZoxYY7WR8PT2ePWn0oJNqAiycbCfnWPRxRvL8ihx1HNMwo0moWLts7zLm3DbrSOS\nsyLSB/xIRF4tIs8F1l7lWm4G9onIXhEZAq4AgjPibwCu8rK3Hg+cUNWj9Y4VkX2+4y8HfhCiLLES\ndY0Ky8bBeIQbczNFNnhijUHK/vMU9mKikMsXucA3YcvP1OQIM/PRjOfp0jJnFldiiZHEJdyYzc+v\nCcBapiczZI8VWYl5zfpOYmN/ta45Dv0pO7k4nhhJdOFGK9ZYrVNoxRvTOPIMu2b7MPBa4NHAC4EX\nNzpIVZcwbqcvAt8HPqWqd4rINSJyjbfbjUAOOAh8EHhlvWO9Y94mIneIyO3A073ytZVCTME5sPLT\n0UYL2WPz7PXEGoNU5CTSd/NFwcynqD7DNw7jGYfOlqWSVNF6Pasq9wQmqfmZnhzh9GJ8+lNpwMb+\n6l1zLh/NeMaVOAOVUU2UkWetmJAlzrTnOGkokaKqNwOIyIqqvqSZk6vqjRhj4d92ne+9Aq8Ke6y3\nve2urCCFGAQbLaMxZHrkZopceF71xZes/lQvuT2WV5R7ZxZ48k9sr/q533i2qgIcZwMzmok+67ks\n1lird+4LPlcbmXYj5YXa6lyzNZ6tXnMcgo0Wfzr/jhbLUyuhwjI1meFrdx9jaXkl8vymOAmTtfUz\nInIXngtJRB4pIn+TeMlSSlyCjZaoC+LUmrBlGezv44Jtwz2V0XN/YYHS8krNa47DeMalpwYV4cYo\nPdXy3IIavfOH9ODk0/JCbRONjWerxCHYaCkvYhbhec4eK9aM/YExMIvLmjrxxjAm7d3AM4DjAKp6\nG/CkJAuVZuJsYMD0eKP4zquJNQaJU38qDVSG/9UbmLIvOYLxtI1+HEFYK9wYpZ5zNeZTWCY3b2Dz\nhoHequeZ1WKNQR4Sw/wZI9g4FMu6JnEsn52bWS3WGMRmbqXNwxBqbKSqhwObek+LISRxCTZaoo5I\nsuX5FLXzH6YnR1K9lkGzBNenqMbURLQspjjTQsHESaLWs1+sMYjVn0qj/7xVssfm2buteuwPjPEc\n2TAQKf5nBBvj8y7Yc7ZK9lhxzdwoP1a8MW0ehjCG5LCIPAFQERkUkd/BBMDXJZV0wfhiJFGEG22j\nGpxb4Gd6MpPqtQyapZpYY5Dp7RnunWldvDEuwUbL6PBgpMlq1cQag/Ta5FOzvG7t+9pMuM2UYymt\nEIdgoyWqcGNwobZqjGWGGM8MdeWI5BpMQHwHZi7HRXjZVeuRcgMTcy+mVeHGXL7IOVtWizUG6TXx\nxmq6YkEqCwG1tt5LoVhi66bB2AKaUYUb/UsK12J6+whHT5xh/mx0/alOE1yorRZR19wpLMSjXgDQ\n3yeRhBuDC7XVYmoi030jElWdUdUXqOo5qrpdVV8IXNWGsqWS2RhWzfMzFlG40cyCbdCoxihkmAay\nddJgLeWFgFp09cwuLMbm8oBoyyqfLi1zZO503Z4qVLSZ7ukB91aY2B+Ye/uBE2daFm+cLcYzudgS\nxYWZnakfB7NMT6Zv8mmr3a3Xx1qKLiLO+QX+87Ry86lqVVnxIKPDQ0yMDPWE//zE6UVm5s/WTAm1\nlH3JLRrPQjE+lwdYQb/FluY8WGHCho3q9ujB57QQJvYHlUa3FfHGOAUbLVHS+ctJJA06SVOTGSPe\nGMPaJ3HRqiHpveX2QhKXYKOlItzY/M13vIZYYzV6JXOrnL3U4GGLKt4Yp8sDKsKNp1oQbgyTXABw\nwbZh+qQ3Jp9WVH8bN6pm/+brOU7BRkuUCcbZGmKNQcoK1ynqMLRqSHpHh6FJ4hJstFSEG5u/+RrN\ngvUTl/5Up2mU+usnSvA5LsFGSxSBzly+ulhjkA0D/eweH+6Zep7cXD/2BxXxxlb0p+LOzINo6fzV\nFmqrRlzKx3FS05CIyCkROVnldQpo+6qEaSEuwUZLFNdWPbHGINOTI8wWS7GtKd0pcjPzDPQJF2yr\nPmHLT5R02LgEGy1RhBuz+Xl2jFYXawzSSyPPRkFnqIg3tmI84xRstFjhxlbWngkuKVwLK96Ypnqu\naUhUdbOqbqny2qyq0aeBdilxCTZarHBjKw18Nj/PhoG+UHIMvbL4UfZYkd3jwwyGyKaa9sQbm10I\nKE7BRstYhDkGuZn5UCMwMCPPe2aKsaxZ3ykqC7WFvebWlg2IU7DRUhZuXGxuql2thdqqYdUq0qQC\nnB6xli4hTsFGi0kNbc21tXciQ1+NCVt+KvpT6RkOt0IzjWqrCwFZ91OcMZLx4dZcmDahIkzvHEyj\nenZphQfmunfOUK2F2moxNdGaeGPcc8LMuVpbrK7WQm21mEqZeKMzJE0yG6Ngo2Us01qmRzbEfArL\nzrFhhvr7UhWgaxYr1hj+YWvNlzybhO+8ReHGB0+eYaG03LTxTJPbo1nqLdRWDb94YzNU5oTFOyKB\n5uu5kQROkOnJEe49XkyNWoUzJE2wuLzCqTNLsY9IxlrIPS8trXC4cDr0w9bfJ+xN4USmZmgk1hhk\nd4u+5PKIJMYOw0iLwo3lnmqDQLslzavohaUc+2swP8rS6rIBs8X4BBstYy0KN+by9cUag0xNZlIl\n3ugMSROUfaoxBuegtSU67YStsCMSsMHnbu6phk8ugIp4Y7MNTKEszBlfPVvhxmZ7quVrbjBvxjKe\nGWJ0eLDLRyTzdcUag7Q64bawEJ9go6VV4cZsfr7mQm3VmE7ZyNMZkiaIezKiZbyFBubgseaG/2Bu\nvvtmF1hMyXC4WZpJ/bW0kgKcRFoomDhJsw1MzhNr3L65ulhjEBFhaqK7Owy5fLGuWGMQq3zcdCws\nRsFGS6vCjWEmFvuZTlkKsDMkTVBIIDgHFeHGZhr4XEg5BT/T2zMsrSiHjremP9VpsvkiYyEmbPmZ\nmsxw6Hhz4o3lGElMgo2WVoQb7fK6zfSajfFMRwPTCrmZYlniJgxW+bjZa56NUbDR0opwoxVrbMa7\nMDpsxBvdiKQLiVuw0VIWbmzi5sseM2KNIxvC+3ejyoZ0GquA2wytiDfOLcQr2GgZzwy1FCNpNIs/\nyPT2EfKnmk97TgPlhdpCxkcsUy2kAM/FrF4AFeHGZkYkVqyxmREJmFGJG5F0IXELNlqsq6yZGbG5\nmcZijUGmWvQlp4Vm0mAttmfbzDXPLizGXsdA04tbhRVrDDLdYtpzGijH/poYkUBr4o1GsDH+em7W\nhRlWrDFI1DV34sQZkiZIMkYC4TM9ynMLmnzYNm8c5JwtG1LTi2kGK9bYysMGzfmSjTxKvKNOsA1M\neOHGRut31yKNEhphKcf+WhiRQPhrVlVvTlj89dys0nN5SeFmOwzb0yPe6AxJExSKJYaH4hNstNhG\nK+zNZ8Uam33YwDyg3TgiCSvWGMQuBNTUiKQYv8sDTD03I9zYjJaan1bTntNAJfbX7IjEKjeEMyQn\nzyyxHLNgo2VseLAp4cbcTOOF2qpRdlWnYFTiDEkTzCYwqx2aF24szy0ImRLqZ3p7huyx+Za0gDpJ\nlGuemmguEDuXQBAWmhduzObnQ4k1BrESGl1pSPJFtocQawxywbZhpAnl47iXzPbTrHBj9lj4icV+\nKmoVna9nZ0iawKxRkcBQuEnhxmyLvXMwPbeTZ5Y43mXijdm8EWsMO2HLT7NaTLMJujzs+cOQyxdD\nizUGSZuERlhMQkXz9/XGwX52jQ2HHpHYZy2J53m8SeHG3EzzCRVgxBsH+yXSUsNx4QxJE9gJTHHT\nrHBjrgmxxiDliUwp6MU0Qy5fZPe2cGKNQcoLAYXIYkpCsNHSrHxGMxI4QdImoRGGiq5Ya9c8NZkJ\nfV8nFe8Ek5obVrjRijW2MtIe7O9j93g6xBudIWmCJAQbLc2khmabEGsMEmUhoE4SZknhWjQj3piE\nYKNlvImRp6pyz0xzk9T8THsSGodTIqERhnLsr1VDMjHCPTPhxBsLCWVgmnOaUU6Yeg67KmIt0jJn\nyBmSJkhCsNEylhkMPY8kF6Gnev7WTWwc7EtFLyYsS8srHDq+0HSWmqUZ/amKyyOJ9F/TwISp52bF\nGoO0qnzcSZpVwA0yvT28eGN5RJLgyDNMPTcr1hhkanKEQykYeTpDEpKkBBstYYUbzy4tc7hwuuWH\nra9Pui5z6/7CaUrLK6FF/ILYhYCaGZEkUc/NCDdacc2WG9UunDPUrJZakGYm3M4WSwz0CZubmNAb\nlmaEG23sL8xCbdVIy8jTGZKQzCUg5OcnrHDjfZ7cR6s9GKAlOYlO0mpKqKWZLKYkBBstzQg3tjqH\nxDI6PMTEyFBXqT3nPLHG81uI/UFl8mmYJIPCwiKjMQs2WpoRbszlwy/UVo20jDydIQlJEmsX+Akr\n3JgtD/9bNyTTkyMcLixwpslV3DpFLoZrDpvFZOsgsVhYyA5D9tg8IxsGQos1VqPblt21cjBhxRqD\nTI4Y8cZQHYZivEsp+2lGuLEV2R8/aRl5OkMSkiRWU/MzNjwUSrjR3jB7W+ydg5mLoUrXiDdm8/OM\nDQ9G8mdPTWZCZTHZet4as2CjZSwTTrgx5wXao/SYpyczqUgNDUurqb8WK94YpsMwu1BKrFMYVrix\n2YXaqjE6PMS2zFDHU70TNSQicomI3C0iB0Xk2iqfi4i81/v8dhG5uNGxIvKXIvIDb//PiMhoktdg\nSXICE4QPxObyzYs1BrEZIp3uxYQlGyEl1DI9ORJqIaBCQoKNlrHhcNl52WPzLWfyWKYnR5gtlppe\nZKkTVGJ/0es5VCwsIfUCCC/c2OxCbbUIazyTJDFDIiL9wPuAS4ELgStF5MLAbpcC+7zX1cD7Qxz7\nZeCnVfURwA+BNyV1DX6s5EESE5ggvF81N9N6xpYlTTNiw5CL2FMF3/oNDeQkCgkJNlrCxEgWSks8\ncOJMLI0qdN5/HoZK7C96oxpGvLGwkIxgo2U8RIchDpetPb7TncIkRySPBQ6qak5VS8AngMsD+1wO\nXK+Gm4BRETmv3rGq+iVVtXfJTcDOBK+hTJLZPBDOr6qqpqca8WEbHhpgx+imrnB7GLHGUiQ/Mvgy\nehoEn5MSbLSMDw8xd7q+cOM9M80v4FWNbhJvLK/T3mJmniXMsrtJCjZawig9ZyOm/lqmJjMcL5aa\nkmWJmyQNyQ7gsO//+71tYfYJcyzAS4EvVPtyEblaRA6IyIF8Pt9k0deSlGCjJYxw4/FiiZNnliL3\nYMBmbqW/p5qLmBJqseKNjUYkSQk2WsIIN5YTKlqcN2PZOTbMUH9fd9RzxMw8i22U611zkoKNljDC\nja0s1FaNyrK7neswdG2wXUR+D1gCPl7tc1X9gKruV9X9k5OTkb8vKcFGS0VKvvbNZ11RUXsw4A2H\nu0C8sdxTjdjAgHFvNRqRJCXYaBkPobeV88Qa92yLds39fcLeie7oMGSPtSbWGOSCbcP0Sf0RSdLx\nTnvuRi7MXMSMLUsaUoCTNCRHgF2+/3d628LsU/dYEflfwLOAF2ibWsKkBBstYWIk1hUVNQgLplEt\nlpY5dups5HMlSS6CWGOQMAsBzS4kp14Alclq9eo5G0GsMUgaArFhiCP2B0a3budY/TlDSWdg2nMX\nFuoLN2ZbWP2yGrvGNnVcvDFJQ3IzsE9E9orIEHAFcENgnxuAq7zsrccDJ1T1aL1jReQS4A3AL6lq\n2/JXkxJstGwc7Gd4qL5wYxSxxiBlF0DKA+7Z/HzLYo1ByuKNNTLjrGBj0jESqB8LiyKBE2R6coRD\nswuUltIr3hhX7M/SyHgmtWS2n7FMfeFGu1BbK2KNQQb6+7hgW3jByiRIzJB4AfFXA18Evg98SlXv\nFJFrROQab7cbgRxwEPgg8Mp6x3rH/DWwGfiyiNwqItcldQ1+Cgn3VKFxamgUscYg0yF8yWkgihps\nkPI11xiVzCYo2GhptGTAyopRwI2rUZ3enmF5RblvNr2jkjhjf2DquZ54Y1JLZvuxgfxa9dzqQm21\nmJro7Jyh+IVmfKjqjRhj4d92ne+9Aq8Ke6y3/SExFzMUs8VkYyRgJ6vV76k+bMfWWL7rnC0byAz1\np1oqZWl5hXuPF3nKT22P5Xz+LKaLd4+t+byQoGCjxbpHa7m2Hjx5htOLy/Ebz3yRh2zfHMs546YS\n+4tvRHJ6cZmjJ89UHb3PJSjYaKksGbDIzrW3WqSF2qoxvX2E/7j7GEvLK4nNgapH1wbb20nSgo2W\nMW9N72qcXVrmvtkFpmPqwYgI09s7n39ej/sLp1lc1pbFGoPYhYBqXXPSKd5ghBsH+6VmPbe6vG4t\n9nbB5FPbk47beNYKPicp2GhptBpmbia+2B+YEUknxRudIQlB0oKNlnrCjfcdX2BF4+vBgDccTvGI\npCxcGDEN1tJoIaBKEDa5ehYRRutk9NgG/yExNaqbNw5yzpYNqRZvtLG/VsUagzSacFvw5FGSEGy0\njDZInskea32htmrYdqFTmVvOkIQgacFGi12isxqV5XXjMyTTkyMcmTvdcBZwp7CNX5zXPFVnISDb\nYUh65DleZ8mAXN6INU5GEGsMkoaZz/Wwsb9WxRqDWPHGWjGDQnEx8U7heAMp+dxM6wu1VWO6CQn9\nJHCGJATtSBcE04CdqiHcaBu/KGKNQWwv5p6UznDPzcwznhmK1Zc9XWchoNliCZHkBBst9RYxy+aj\nizUGMVlM6Z0zFGeWGnjijdtrqz0nPScMKsKN1VyYcYg1rvm+4cGOijc6QxKCdkxggopLpVojk8sX\nOXfLxkhijUHSvuxu9lg8efZ+puosBFRYKLFlY3KCjZZ6yyrH3aiCMZ4nzywxM58+8UYb+4srJmSZ\nrjMRs9CGxJn+PmG0hnCjFWtMop7diCTFtCNdEOr7VaNKbFdjz7YMIumdS5Kbif+a6wVik1xK2U+t\nGIkVa4zbeKY51dvG/mKv5+0jHD1xhuLZtW7bQsLqBZZa6fxxJ1RYOjn51BmSELRjAhPUFm5U1UR6\nqhsH+9k1NpxK8cYTC0asMf5eW20hw7mFxUSF/Cy1hBvjTgm1pFm8MY6F2qphjXHQbWsEG5OPkUBt\n4caoSwrXYnpypGPijc6QhGA2YcFGSy2ZlJl5M2Er7h4MeOKNKRyRZGfi0xXzMzpsxBur9c7bMVcI\nTANTTbixLIETcz2fv3UTGwfTKd5YXqgtdhdm9VGYFWxsSz0PD1XVzrNijXGPijrpqnaGJASFNgTn\noDJZLXjzlWfBxtyogrcQ0Mx8XVnzTlBZqyF+4zldwwXQPpeHV8+BDkP2WDxijUH6+oSpiXRmbtmF\n2qKKNQax4o3BRjXppZT9jA1Xj5FEXV63Fp0Ub3SGJARJCzZaao1IKhO2kmhURzizuMLRk2diP3cU\nsp5Y466YJmz5qdWotkMGByozqoOpobmZIjvH4hFrDJJW8cZsPt40WIsVbww2qvbZakc926SKYLac\nkf2J/1m24o1uRJJSZhMWbLTUEm7MHptn42Af52+NZ8KWn7SulpjLz3NBjBO2/ExvX7sQkBVsbEc9\nWy2voC/bLK8bf6MKpsNwuLDAmRoigp2gHPuLacJpkGojz0Ib5FEsY5khSgHhRivWmMSIxIo3uhFJ\nSplrU08Vqmd65GaK7J0YiUWsMUhaM3rMfIpkGtXyaom+Rma2nOLdvpGnf0SysqLcMxOfQGWQ6e0j\nqMK9x9MzKinH/hIynlNV3LblJbPbUs9rhRvjWqitFtMdWrDOGZIQtCsIC9WFG5NI/bVMjAyxZeNA\nqtweS8srHDoenwJukGpyEu0QbLRUE260Yo2JXXMKM7cqsb+krnmt27Ydgo0Wv3CjJanUX8vU5Aj3\nzS5UnXCbJM6QNKBdgo2WoHDj2aVlDs8uJNaDERFPNiQ9I5KyWGNC11xtIaB2+s6rCTcmlRJqKYs3\npsiFGbdYY5Bqbtt2CDZaqgk32thfXGKNQaYnRzoi3ugMSQPaJdhosSurWcpijQn1YCB9WkyVRjWZ\nax7wxBuDDQy0x+UhImuWYk0ySw1geGiAHaOb0lXPx+JbqK0alfkzvpFnGwQbLdVWw8zl4xVrDNKp\nmKczJA1oZ3AObO756h4MxCtcGGR6e4YfnzzLqTO114tvJ+Xhf5LXPDmyekTSxrRQ+z3Beo5brDHI\n1GQmVXI4JvYXz0Jt1Zgc2cDmjavFG416QXs6hdViYUllqVmseGOjJaXjxhmSBsx2oIHxCzdmE/ap\nQsW1kBbxxmw+frHGIFMB8cbCwmJbBBstY5nBNT3V6ZjFGoNMT46kSrwxm4Bag59qbtukl8z2UxZu\n9FKwBXIAABBqSURBVNoQE/tbSCxLDYx448TIUNuXDXCGpAHt7qkGhRuz+XnO3bKRTII+3enyjNh0\nuD1y+fjFGoNMB8Qb2yXYaDEuzNUxkqSy1CzTkxmKpWV+fPJsot8TBhv7S7KDBGtTgNsh2GgpCzd6\n9Xx/4bQRa0xwRAJmJO9GJCmjsNAewUZLULgxly8m2oMB2D1u1oJIy+JHuZlke6rgk9DwfMntEmy0\n+IUbF0pLHD1xJtE4GKQr1bsS+0vaeK4Wb2yXeoHFn84f90JttZje3v7Jp86QNKBdgo0W/4I4qpq4\nTxVgaKCPC8aH296LqYYVa2xHTxUqD3e7BBst495qmCsr6ksJbY/x7NQqen6yCaf+Wvzije0UbLSM\nZSodhnbE/uz52y3e6AxJA9ol2GgZ8816npkvcSohscYgRryx8yMSK9aYdE91dHho1UJA7R6RjGWG\nWFE4dWapbY3qOVs2kBnqT0XAPdsm42nnDGXz820VbLT40/mz+flExBqD2BFPO+vZGZIGtEuw0VIZ\nkSwmPgvWz/TkCPccL7LcYfFG62pqm/H0fmObFtoubK94dqFELl9MRKwxiIgwvT0dqd7Z/DznbNkQ\n60Jt1fCLN7Y73gmmnu33ZvPJKRf4merAsrvOkDSgXYKNFutCKyyU2pKxZZmeHKG0tMKRNk9kCpKb\nKTLYn4xYYxCTxdSZEcmoLzU0m59PTKwxiP+aO0muTY3qhoF+do0b8cbZNk46tdgYidUVa8ezvNNO\nuHUjkvTQLsFGi1+4MZdPTqwxyFRKMreyx+bZPZ7chC0/U5NGvPHoidOcXWqPYKPFL9zYrkYVTMzg\nyNxpFkprVw5sF+XYXxsaVTDXnM0X2yqPYrHCjQ+ePJPIQm3VGOjvY8+29mpuOUPSgEKbe6pQ6cVk\n8/OJiTUGSUtGT24mObHGIPaaD9xbANozq91i76nj8yWzpHDCAVhLRWesc6OScuyvXdc8OcI9M/Pl\nNevbnVQBlXusXfe2WTbAGZLU0O4YCVSEG3MzyaxbUP077cqBnWtgrFhj23rn3vfccsgzJG11bZnG\n7K6jJzmzuJJ4SqilvGZ9ByeflmN/MS8pXIspT7zxrgdOAp2pZ3uPtet5nvbEGxfbJN7oDEkd2i3Y\naBkbHuLBk2e9CVvtedjAugA6NyI57Ik1tsvlYcUbDxyaBdrrO7fCjfa729U7v2DbMCKdFW8sx/4S\nnnRqsffTLYcKbRNstNh76sCh2cQWaqvGlBVvnF1oy/c5Q1KHiiJs+4bC5vuG+P7Rk4mLNQaxEhqd\nop1ZalBZCOiOI15PtY0dBivcaL+7XfW8cbCfXWPDHe0w5PLJijUGsffT/xw5wVimPYKNFjv6uePI\nyUTFGoNUBCvbM/J0hqQOVqaknUNhWN2gtatRBZN/PjNf4sRCZ8Qbk1b9rYa/V9xO3zlUequbExZr\nDDLdYfFGE/tLTqwxyMTIEJs3mlFI2+u4U89ym1OAnSGpQ7sFGy3+79vbpuE/+ALuHZrhnssXGc8M\ntXU+h99P3y7BRov1n08lLNYYZMoLPq90aM5QLsGVIKshIuXva/ezvMV3T7XLZQsV8UY3IkkBnZjA\nBBVX2mC/JCrWGCSoP9VurAJuO/GPSNol2GixI5J2Nqr2+84srvDAifbPGaos1Nbmeva+r90ZmP2+\nUVe769kuNdwOEn1yROQSEblbRA6KyLVVPhcRea/3+e0icnGjY0XkeSJyp4isiMj+JMvfbsFGi3Wl\ntbNnDpXgc6fcHu3QFQvSzmSGIBsG+r0ytLdRrag9t7+eD3lije3+3W0jPjTQub5zu41nO12Yif2q\nItIPvA+4FLgQuFJELgzsdimwz3tdDbw/xLF3AL8MfCOpslvaLdhosSOgdvtz7USmTgTc5xZKHC+W\n2pYGa2n3w+3HTpDb00b3JVRfs75dtDuhwmJHnoUOxf9MGdpvPGeLpVUrcSZFkn6TxwIHVTUHICKf\nAC4H7vLtczlwvZqVdm4SkVEROQ/YU+tYVf2+ty3BohvaLdhoGfCGw7vG2pMq6GdqMsPX7s7zlHd8\nzWxQUMxsZOtRVwVFzV+fm93u4//cO4X3Pritsr/117f7YWv3qM+PvYfP3bKxrd+7LTPElo0DvOer\nP+KjNx2CGnVitq2uZ7soVrCe/fcGvm3B/c8uLQOwt80G/Nyt5jduXyRqLe1O2ilnbs3M8+jMeKLf\nlaQh2QEc9v1/P/C4EPvsCHlsXUTkaswoh927dzdzaJl920d41iPOa+nYKDz6gjFe8fNT/MYT97b9\nu1/8hD0M9HkDVTEPnoh4f8uby9vMPhL4rLJN7E7l7YHPve8VETIb+nnivom2XKeftz/vkW1vzAHe\n+pyf5sLv3Mejdo+19XtFhN9++k/w3XtmvQ1r69lfL8F6rny2tp5r3gdUDOf09pHExRqDPHLnKK95\nykP4tcfsauv3Anz8ZY/jgbn2x6Mees5mnvGwcxjqT74jLEktuykivwpcoqov8/5/EfA4VX21b5/P\nAW9T1W96/38VeCNmRNLo2K8Bv6OqBxqVZf/+/XrgQMPdHA6Hw+FDRG5R1Yax6CS7BUcAv/nf6W0L\ns89giGMdDofDkQKSTGG4GdgnIntFZAi4ArghsM8NwFVe9tbjgROqejTksQ6Hw+FIAYmNSFR1SURe\nDXwR6Ac+rKp3isg13ufXATcClwEHgQXgJfWOBRCR5wJ/BUwCnxeRW1X1GUldh8PhcDjqk1iMJE24\nGInD4XA0T9gYiZvZ7nA4HI5IOEPicDgcjkg4Q+JwOByOSDhD4nA4HI5IrItgu4jkgUMtHj4BzMRY\nnLhw5WoOV67mcOVqjrSWC6KV7QJVnWy007owJFEQkQNhshbajStXc7hyNYcrV3OktVzQnrI515bD\n4XA4IuEMicPhcDgi4QxJYz7Q6QLUwJWrOVy5msOVqznSWi5oQ9lcjMThcDgckXAjEofD4XBEwhkS\nh8PhcETCGZI6iMglInK3iBwUkWvb8H33isj/iMitInLA2zYuIl8WkR95f8d8+7/JK9vdIvIM3/ZH\ne+c5KCLvlSbXJRaRD4vIMRG5w7cttnKIyAYR+aS3/TsisidCud4iIke83+xWEbmsA+XaJSL/ISJ3\nicidIvK6NPxmdcrV0d9MRDaKyHdF5DavXH+Ukt+rVrk6fo95x/aLyH+LWRCw47/XKlTVvaq8MPL1\nWWAKGAJuAy5M+DvvBSYC2/4CuNZ7fy3w5977C70ybQD2emXt9z77LvB4zAqnXwAubbIcTwIuBu5I\nohzAK4HrvPdXAJ+MUK63YFbKDO7bznKdB1zsvd8M/ND7/o7+ZnXK1dHfzDvHiPd+EPiOd+5O/161\nytXxe8zb//XAPwCfS8szWS5bMzuvpxfwM8AXff+/CXhTwt95L2sNyd3Aed7784C7q5UHs3bLz3j7\n/MC3/Urgb1soyx5WN9ixlcPu470fwMy6lRbLVeshb2u5At/9/4CnpeU3q1Ku1PxmwDDwPeBxafq9\nAuXq+O+FWSX2q8BTqBiS1PxezrVVmx3AYd//93vbkkSBr4jILSJytbftHDWrRgI8CJzToHw7vPfB\n7VGJsxzlY1R1CTgBbItQtteIyO1iXF92eN+RcnkugUdherOp+c0C5YIO/2aem+ZW4BjwZVVNxe9V\no1zQ+Xvs3cAbgBXfto7/XhZnSNLFE1X1IuBS4FUi8iT/h2q6Cx3P105LOTzej3E/XgQcBd7RqYKI\nyAjwL8BvqupJ/2ed/M2qlKvjv5mqLnv3+k7gsSLy04HPO/J71ShXR38vEXkWcExVb6m1T6efSWdI\nanME2OX7f6e3LTFU9Yj39xjwGeCxwI9F5DwA7++xBuU74r2Pu9xxlqN8jIgMAFuB460USlV/7D38\nK8AHMb9Z28slIoOYxvrjqvppb3PHf7Nq5UrLb+aVZQ74D+ASUvB7VStXCn6vnwV+SUTuBT4BPEVE\nPkaKfi9nSGpzM7BPRPaKyBAmAHVDUl8mIhkR2WzfA08H7vC+88Xebi/G+Lnxtl/hZVvsBfYB3/WG\nuidF5PFeRsZVvmOiEGc5/Of6VeDfvR5V09gHyeO5mN+sreXyzvN3wPdV9Z2+jzr6m9UqV6d/MxGZ\nFJFR7/0mTNzmByn4vaqWq9O/l6q+SVV3quoeTDv076r6wk7/XsFCulftANdlmEyXLPB7CX/XFCbT\n4jbgTvt9GD/lV4EfAV8Bxn3H/J5XtrvxZWYB+zE3exb4a5oPyv4jZgi/iPGj/kac5QA2Av8EHMRk\nkUxFKNdHgf8BbvcehvM6UK4nYtwKtwO3eq/LOv2b1SlXR38z4BHAf3vffwfw5rjv9ZjL1fF7zHfe\nX6ASbO/4M2lfTiLF4XA4HJFwri2Hw+FwRMIZEofD4XBEwhkSh8PhcETCGRKHw+FwRMIZEofD4XBE\nwhkSR08gItukos76oKxWax0KeY6PiMhPNNjnVSLygpjK/E0RuUhE+iRmdWkReamInOv7v+G1ORyt\n4tJ/HT2HiLwFmFfVtwe2C+aeX6l6YJsRkW8Cr8bk9c+o6miTx/er6nK9c6vqrdFL6nDUx41IHD2N\niDxEzHocH8dM9DxPRD4gIgfErDnxZt++doQwICJzIvI2MWtTfFtEtnv7/LGI/KZv/7eJWcPibhF5\ngrc9IyL/4n3vP3vfdVGdYr4N2OyNnq73zvFi77y3isjfeKMWW653i8jtGC2oPxKRm0XkDhG5Tgy/\nhtGF+qQdkdlr8879QjFrUtwhIn/qbat3zVd4+94mIv8RcxU5egBnSBzrgZ8E3qWqF6rRM7tWVfcD\njwSeJiIXVjlmK/B1VX0k8G3gpTXOLar6WOB3AWuUXgM8qKoXAm/FqO7W41rglKpepKpXiREKfC7w\nBDUCggMYaQxbrm+o6iNU9dvAe1T1McDDvc8uUdVPYmax/5p3zlK5sCI7gT8GnuyV62fFiALWu+Y/\nBJ7qbX9ug2txrEOcIXGsB7KqesD3/5Ui8j3MehM/hVkIKMhpVf2C9/4WzDoo1fh0lX2eiBHXQ1Wt\n5E0z/CLwGOCAGEnznwemvc9KGEFPy1NF5LsYaZ2fBx7W4NyPw+gozajqImahJKsyXeuavwVcLyIv\nw7UZjioMdLoADkcbKNo3IrIPeB3wWFWdE6OiurHKMSXf+2VqPytnQ+zTLAJ8WFX/YNVGo8p6Wr3A\npogMY/SSLlbVIyLyx1S/lrDUuuaXYwzQs4DvicijVLUQ4XscPYbrXTjWG1uAUxgV1POAZzTYvxW+\nBTwfQEQeTvURTxk1CwlZQwFGgO/5IjLhbd8mIrurHLoJs9DRjBjl6F/xfXYKs7xukO8AT/bOaV1m\nX29wPVOqehPwB0CB5Bd4c3QZbkTiWG98D7gLI1t+CNPox81fYVxBd3nfdRdmxbl6/B1wu4gc8OIk\nf4RZLbMPo3Z8DfCA/wBVPS4if++d/yiV1Q8BPgJ8SEROU1k/A1W9X0T+APgaZuTzr6r6eZ8Rq8a7\nxMiRC/AlVb2jzr6OdYhL/3U4YsZrlAdU9YznSvsSsM+OPByOXsONSByO+BkBvuoZFAFe4YyIo5dx\nIxKHw+FwRMIF2x0Oh8MRCWdIHA6HwxEJZ0gcDofDEQlnSBwOh8MRCWdIHA6HwxGJ/x/OY5sBCSoF\nDgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fbf6d3de6d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xlabel('Training Iterations')\n",
    "plt.ylabel('Learning Rate')\n",
    "plt.title(\"CLR - Custom Sinusoidal Cycle-Policy\")\n",
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr = lambda x: 1/(5**(x*0.0001))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(scale_fn=clr, scale_mode='iterations')\n",
    "\n",
    "model.compile(optimizer=SGD(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7f8f2fa954a8>"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular],verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f8f2fa956d8>]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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BtWcM/8x735o/korqelZsymuhtjFt86aJ7GWgL/A28JrHZnzo3TAZntzU3JED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\nggkhhFATkWBCCCHUxH+w+kycHWZ6PwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8f2fa95710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xlabel('Training Iterations')\n",
    "plt.ylabel('Learning Rate')\n",
    "plt.title(\"CLR - Custom Iteration-Policy\")\n",
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### RMSprop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='triangular')\n",
    "\n",
    "model.compile(optimizer=RMSprop(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcf0088c278>"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular],verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef2275128>]"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SMD66OY6ZNJLZmVFakO1J2Z2ijnheZhcPB0ICudgbldl5dTWl7eCTDdmddyYv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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef3a13748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='triangular2')\n",
    "\n",
    "model.compile(optimizer=RMSprop(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcefa6e87f0>"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=20, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular._reset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcefa6e8828>"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef2a169e8>]"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2SwuEaINS8S3szFYePjHOqs52BleuqPhYv6+Ni3o61bGslM18lnJj5kq/nYun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\n5FGBoCiKogDwfwAC8F0kV6KlTAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcefa6e8dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='exp_range', gamma=0.99994)\n",
    "\n",
    "model.compile(optimizer=RMSprop(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef3825be0>"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=20, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef39234a8>]"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Ikn4Fx2ZuRJvdpHpBuDKWfIVyPJ01pZj1rMLpWVV6WTnj3V4nDjXY8EhHJYJhge4Jd66X\nxDApw4KQJAOzXpgLDai0rD8qUglaHSZML63AtxrK2DXS5cr4IhrLS1Bu2npPok6phUW+WAlz3lV0\nT7rx0E4HDjeWAeDAMqNtWBCSpN/pRVuleUuB1K0i90hSc6bRlTF3Su4iIFqLAOSPILzf74IQwMM7\nHXBYCtFUUcKCwGgaFoQk6VdwbOZGtEoV0ANOdQaWZz0rmFhcxoF6a0rHl5mMqLUW5U2m0bs9TpSV\nFGBvXfR+3NNUhoujC4g2/2UY7cGCkASelSBmllbRVql8y4pYmitMIFJv6unVsah/PFULAYhaCflg\nIUQiAn/sc+GBdgf0uqjVeE9TGVzeAEbn/TleHcOkBgtCEsgtKzJtIRQV6FFnK1ZtT6OrE27oCNhT\nu/HIzM3orC3FgNOn+Wycm9NLcHlX8fDO23O+72niOAKjbVgQkkBOOc1ED6N4oqmn6nQZXRtfRHtl\n4pGZm9FZU4pwRKB3RtuN7t7tdQIAHmq3r21rr7TAUmhgQWA0CwtCEvQ7vSjQExrLSzJ+rVa7CUMu\nn+r80EIIXJtYWvOXp0q+BJb/2OvErmoLKkuL1rbpdYSDjTYWBEazsCAkwaDTi6YKEwqS6P2fLm0O\nE/yBsOrmK08vrcDlXcX+FAPKMo3lJTAZ9ZquWPathvDRyMId7iKZe5rK0DPj4e6njCZhQUiCQadv\nrddQppFTT9UWWL46Hg0o70tTEHQ6wu6aUk1nGp0bmkMwLPBg+/qCIER0ohzDaA0WhE0IRwRG5vxr\nKaGZRr6O2uII3RNu6HW0VlyWDtFMIw8iGp2N8H7fHAoNOhxpLrvrtYMNNhBxYJnRJiwImzC+4Ecg\nHEGbPfMBZSA6X7nEqF/LbFILV8fdaK80o6hAn/a5OmtL4V0NYXxB/bMf1uP9fieONpevey8sRQXo\nqLKwIDCahAVhE2TXTbYshGiTO3WN04wGlN1pxw9k5MCyFt1GM0sr6J3x4oGY7KJ47mkqw6XRxbyc\nDsfkNywImyBXDbdmuAYhlla7ulJPJ90rmPcFsC/NDCOZjioLdKRNQfig3wUAeGBHYkHwroY0n1rL\nbD9YEDZh0OWDraQgpWZuqdLqMGFicVk1xVvXpJGZ+1LocLoexUY9Wh1mTWYavd/nQrnJmDCWwgVq\njFZhQdiEQacXrVnKMJJpdZghhHqa3F0dd8OgI+yqtih2Ti22sBBC4P1+F+5rq4BOt3GTw8byEtjN\nRlxkQWA0BgvCJgw6fVl1FwFYEyC1pJ5em3BjZ5VFkYCyTGdNKSYWl+H2aydfv2/Wi1nPKh5MED8A\nonGgw41l+IhHajIagwUhAZ6VIGY9q1mrQZBRU+qp0gFlmU6pH9LNae1YCe/1SfGDdeoP4rmnqQwj\nc/68GgbE5D8sCAkYdkW7VrZlKcNIpsRoQI21SBWZRuMLy1j0B9NuWRHP7pqo+0lLcYT3+5xosZtQ\nZyvedF+5RuEiWwmMhmBBSIA88D7bLqPoNU2qsBCuSSMhlbYQKi1FsJsLNZNpFAhFcG5oPmF2USx7\naq0w6nUcWGY0BQtCAgacPugIaKrIfFO7eKKpp7lvcnd13I0CPaFDwYCyTGetdgLLl0YX4A+EE9Yf\nxFJUoMfeulJ0Dc9neGUMoxwsCAkYdHpRX1aCQoNywdRkaXWY4FkNwenNrQ/62sQiOqotGbkHu2ss\n6JvxIhCKKH5upXm/3wUdAfe2VSR9zNHmclybcKsmfVhJ/tvbfbjnP72FUFj9vzsmeVgQEhDNMMpu\n/EBGDU3uhBC4Nu7Gvjpl6g/i6awpRSAcUe3I0Fje63PhQIMNpUUFSR9ztLkcwbDIu0Z3Qgj83Vu9\nmPMF8u69bXdYEDYgEhEYcvnQmqUeRvGoIfV0dN6PpZWQ4vEDGXny2nWVB5bdy0FcHV/Eg0nGD2Tk\nwHK+uY1iReAPPbM5XAmjNCwIGzC9tILlYDhnFkKdrRiFBl1OA8trLa8VzjCSabGbUVygx/VJd0bO\nrxRnBuYQEcmlm8ZiKzFiZ5UZ54fzK7D868uTMBp02F1Tij/ccuZ6OYyCJCUIRPQ4EfUQUT8RfWud\n14mIviu9fpWIDm92LBH9J2nfy0T0JhHVKvOWlCHbTe3i0ekILfbcNrnrnnDDqNdhZ5XyAWUgOmFs\nd41F9RbC+/1OmIx6HGrcuuvsaHM5Lo4s5E2ju1A4gleuTuLRXZX49IFa3JhawozKhjkxqbOpIBCR\nHsD3AJwE0AngGSLqjNvtJIB26es5AN9P4ti/FULsF0IcBPAKgL9K/+0ox1rKaY5cRkDuU0+vjrux\nu8YCoyFzhuTeOituTC6pejbCB/1zON5akdLEvKPN5fCuhjSTTbUZHwzMweUN4NTBOnxsV9RiereH\nrYR8IZm/8GMA+oUQg0KIAICfATgVt88pAD8RUc4CsBFRTaJjhRCx/0NMAFT1RBh0+mAy6lFVWpiz\nNbTazRhbWM5JFk4kItA94Va8IC2ePdJshJF5f0avkyrjC34MuXxJ1x/Ec7SlHED+xBF+fWkCliID\nHulwoKPKghprEccR8ohkBKEOwFjMz+PStmT2SXgsEf1nIhoD8CWozkLwocVhAtHGTcwyTavDhHBE\nYHQ++26jkXk/PKuZCyjL7KmNnl+tcYS1dtdJ1h/EU2crRq21CBfyII6wHAjjjevTeGJvDYoK9CAi\nPNLhwHt9LgQ5/TQvyGlQWQjxbSFEA4B/AvDN9fYhoueIqIuIupzO7Jmm0S6nuXMXAbdTT3MxPe2q\n3PI6QymnMjurLCjQE7on1OlSOTMwB7u5EO2Vqf8tHG0px/nh+ZwXGabL727OwBcI49Sh2+G+Rzoq\n4V0NoSsPBI9JThAmADTE/FwvbUtmn2SOBaKC8Pn1Li6E+IEQ4ogQ4ojDsbUsj1RZCYYxsbics4Cy\nzO0md9kXhGvjbhgNOrRXZVYUjYZo0FqNFoIQAh8OzOG+toq0LMWjzeVwelYxqlK3WLL8+vIEqkoL\ncbzldnHe/TvsKNAT3mG3UV6QjCBcANBORC1EZATwNIDTcfucBvCslG10AoBbCDGV6Fgiao85/hSA\nW2m+F8UYnvNBiNz0MIqltKgAdnNhTgLL3ZNu7K62pBRI3Sp7a624Prmkuk/QA04fZj2rW6pOXo+j\nzdE4wvkh7cYRFv0BvNvrxFP7a6GPmQVhLjTgWEs5xxHyhE3/twshQoi6c94AcBPAL4QQ14noeSJ6\nXtrtNQCDAPoB/BDAnyc6Vjrm/yaibiK6CuAxAP9BubeVHmspp1lue70ebQ5T1it5hRC4PrmEPRkO\nKMvsrSvFvC+AKbe60hfPDETjB/elKQjtlWZYiws07VZ54/o0gmGBTx+8Ozv8Yx2V6J3xYmJxOQcr\nY5TEkMxOQojXEH3ox257IeZ7AeAbyR4rbV/XRaQGBtfmKOdeEFodZrx2bQpCiKwFuMfml+FZCWFv\nbXYEoVO6TveEG7VJtJbOFmcG51BnK0ZjeXrNDXU6wpGmMlzQcKbRK1en0Fhesm6R4iMdlfg/X72J\nd3pm8aXjTTlYHaMUXKm8DoNOH2qsRSgxJqWXGWVHpRnu5SDmfIGsXVP258utJTLN7hoLdKSuFhaR\niMCZgTmcaE0vfiBztKUcgy4fXDluVpgKLu8qPuh34akDNeveizaHCQ3lxVy1nAewIKzDgMuX9Slp\nG7FDym7pn82e26h70g29LjMtr9ejxGhAm8OsqsDyrWkPFvzBtN1FMkc13Nfo9e5pRATw5P71mwkQ\nET7WUYkP+l1YDeVfZ9ftBAtCHEKIaMqpCtxFwO1pbdkUhOuTS2ivNCs6Q3kz9tSWqspCODM4B2Br\n7a4Tsa/OhkKDTpP1CL+5MokdlWbsSvAB4ZEOB5aDYU0HzhkWhLtweQPwrIRyXoMgU2stRnGBPquB\n5e6JpbWCsWyxt86KKfeKalwqZwZcaK4oUSymYTTocLDBprk4wszSCi4Mz+PJ/eu7i2TubbXDaNCx\n20jjsCDEoaaAMhANSLZVmrJmIcwuRR/K2YofyNyuWM69lRAKR3BucB73tqVWnbwRR5vLcX1yCb7V\nkKLnzSSvXp2CSOAukik26nFvawXXI2gcFoQ4hqTuom05rkGIZYfDjIEsCUK35MfPdA+jeDrXZiPk\nPo7QPbkEz2pIsfiBzNGWcoQjApdGtTNU5jdXJ7G7pnQtlpWIj3U4MOjyYTiHHXqZ9GBBiGPQ5YPR\noFNV+mObw4xJ90pWPllel1pI7K7JTkBZxlpcgMbykrXr55IzA9H4wYlWZQXhcKMNOoJm3EZj835c\nGl3EUwdqktr/kY5KAGArQcOwIMQx6PSipcJ0RzVmrpE/nWWjhUX3pBstdhMsWxgVqRR760rXLJRc\n8uGACzurzHBYlO10aykqwO6aUs0IwqvXpgAAT+5LblRJs92EVrsJb9/KT0G4Nu7Oe7FjQYhj0Kme\nlFOZtdRTpyfj17o+ubTmvsk2e2qtGJnzY2klmJPrA0AgFMGF4Xncp3D8QOZoczkujS5qojvoK1cn\ncaDBhsaK5AvzHt1diXOD8/BqKE6SDJGIwFN//z6++uML8Afy673FwoIQQygcwei8Hy0qCSjLNEkW\ny8BsZi2ERX8A4wvLWatQjkcOZN/IYWD58tgiVoIRxd1FMkeby7EcDKN7IveWUCKGXD50Tyzhqf3J\nuYtkHt1dhUA4gvd68yvbKNbqeeP6dA5XkllYEGIYX1hGKCJUZyEYDTo0lZdkPNNIfhBnO8NIZk9M\nC4tccWZgDkTAidbyjJz/aEu0QE3t+fqvXJkEAHxqi4JwpKkM1uIC/O5mfrlWfvjeIGqtRai1FuHl\ni+s1bM4PWBBiGJqLfgJXmyAAQFulGf0ZrkXoznLLingclkJUlRbm1EL4cMCFPbWlsJUYM3L+SksR\n2hwmnJUK39TKK1encLS5DDXWrSVXGPQ6PNLhwB96ZvNmjvSVsUWcH5rH1x9owZ/cU4/3+12YVlkj\nRqVgQYhBTpdrrlCfIOyoNGNkzpdR3/P1ySXUWItQYc7d2NC9tdacBZZXgmFcGl3EvRlyF8kcb61A\n1/CCah+YvTMe9Mx4Nq092IhHd1dh3hfA5THtVWWvxw/fG4Sl0IB/c7QBnz1cDyGisyHyERaEGIZc\nPlgKDbCbM/PpMB3aHGYEwyKjQ1a6J9xZr1COZ0+dFf2zXiwHst8T56ORBQTCkYwFlGWOt5TDsxrK\nqSWUiFevToEIOLmvOqXjH97pgEFHeeE2Gpv347VrU/jT442wFBWgxW7C4UYb/vXiuOrmdygBC0IM\nQy4fmu25naO8EZlucucPhDDo8uXMXSSzp7YUEQHcms7+w/LDARf0OsLRlszED2TkgPW5IXW6jX7b\nPY2jzeWotBSldLy1uABHm8vx9s0ZhVeWfX78wTB0RPjq/c1r2z53uB69M15VVNUrDQtCDMNzUUFQ\nI5lucndzygMhsl+hHI98/e4c/Gc7MzCH/fVWmAsz2/a8qrQIzRUlODuovsBy/6wXPTMePLE3NetA\n5tHd0aE5YxoeG+pZCeIXXWP41P6aO2IpT+6vgVGvy8vgMguCxGoojImFZVUGlIFoUVNVaWHGmtxd\nX2tZkVsLodZahLKSAtzIchzBHwjh6rj7jnnBmeR4SwUuDM8jorI4wm+7o8Voj+/dWnZRPB/fXQUA\n+J2GrYSXusbhXQ3h6/e33LHdVmLEo7srcfrKhCbqSbYCC4LE2LwfEQG02NObjpVJdlRmrqfR9Ykl\nlJuMqC5NzU2gFESEPbVWXMty6unFkUWEIgLHM5RuGs+JtnK4l4O4mQPXWCJe757G4UYbqq3p/R00\n201oc5jwtkbjCOGIwD+eGcY9TWU40GC76/XPHa6HyxvAe335VW/BgiAx5IqatmrMMJLZ4TBjwOnL\nSDCre9KNPbWlqoif7Ku3omfak9VhK+eG5qCjaB59NpAtkXMqchuNzvlxfXIJJ9O0DmQ+vrsK54bm\n4Mlh5Xmq/P7WLEbm/PhaTOwglod3OlBuMuad24gFQUJOOVWrywiIWgje1RBmlpSdGRAIRdA748l5\nhpHM/jorgmGBnunMt+qQOTc4j7111qz1cKq1FaOhvFhVgeXX19xF6cUPZB7dXYVgWOCPvS5FzpdN\nfvzBEGqTmSzLAAAgAElEQVStRXh8z/r3wmjQ4dMHavHmjRm4l7UneBvBgiAx6PKhrKQgYwVJSiC3\n5FY6sNw740EwLHIeP5DZVx8Vpqvj2XEbrQTDuDy2iOMZzi6K53hLBc4PqSeO8Fr3NPbXW9FQrozb\n9HCjDbaSAs1lG92cWsKHA3P4yr3NMOg3fkR+9lAdAqEIXpeaAOYDLAgSwy71ZhjJ3E49VfaT8+2W\nFeqwEOpsxSgrKcC1LAnCpdFFBMKRrAWUZY63lGPBH0RfFsejbsTE4jKujC0qZh0A0arlj3VUaq5q\n+R8+GEZRgQ7PHGtIuN/+eivaHKa8chuxIEgMz/nQouL4ARBt7WApMmBA4TbY3ZNumAsNaFLok2G6\nEBH21dtwNUuB5fND8yCKNp7LJmqqR/htd7Rhm1LxA5lHd1diwR/ExVFtVC3PeVfxy8sT+Nzh+k29\nBUSEzx2ux/nheYzOaTe9NhYWBADLgTCm3Cuqjh8A0T/ANodZcZfR9ckldNaUQqeiGRD766zom/Fg\nJZj5wPK5oTnsqi6FtSS7MyDqy4pRZytWRV+j169NYXdNqeL/Bx5aq1rWhtvoxfOjCIQi+Np9zUnt\n/9lDdSACXr40ntmFZQkWBEStAwCqdxkBUbeRkk3uwhGBm1O5m4GwEfvqrQhJa8skgVAEF0cXsh4/\nAKICf7ylHOeH5nPaBmFmaQVdIws4qaC7SKa0qADHW8s1kX4aCEXw07MjeLDdjvaq5CYG1tqKcX+b\nHf/y0bhqYkHpwIIAbWQYyeyoNMPpWVUss2Fkzgd/IKw+QZAqljNdj3B1XJ5/kH1BAIDjreVweQMZ\nKzhMBrm//xMp9i7ajEd3VaF/1qv6Wcuvd09hZmkVX3+gZfOdY/jCkXqMLyyrwtJLFxYE3G57rQkL\nQco0UuoBcnMqGqDurFGXINRYi2A3GzOeaXROmktwLMsBZRk5kJ3LNhavXZvCjkozdlRmZo72Jzqj\nVctv3VCv20gIgR+9P4RWuwkPtzu2dOwn91SjtMiAX3SNZWh12YMFAVELwWEpzHgPGyVoU7jJ3Y0p\nNww6WstgUgtEhH111oxnGp0dnMPOKjPKTblJN26qKEFVaeGaMGUbl3cV54fm0+5dlIiG8hLsrinF\nmzfUO2ns8tgiroy78dX7m7ccSysq0OPUwTq83j2t+ZoEFgREu5yqPcNIpqGsGEa9TrEWFjenPGhz\nmFFUoFfkfEqyr96GvllPxlphB8MRfDSykPV001iicYQKnBucy0kc4c3rM4gI4OQ+ZbOL4vnknip0\njSzA6VG2qFIpfnpmBOZCAz53uD6l4794pAGroQh+I02a0yosCIi2rWhWcQ+jWAx6HVrsJgVdRuoL\nKMvsr7MiIqJWTCbonnDDHwhnrX/RRpxorcCsZxVDOfCxv949heaKEuyqzoy7SOaxzmoIAVUWqc15\nV/HK1Sl87nBdyl6CvXWl2FVtwUsadxtte0HwrATh8q6ixa4ul0ki2ipNiriMFnwBTLlXsLsmsw+D\nVMl0xfLt+EFuBUEWpGy7jdzLQZwZmMMn91RnvIfV7hoLGsqL8aYK4wi/6BpHIBzBV040pXwOIsIX\njzTgyrg7J7M8lGLbC8Kw1NROzV1O49nhMGN03p92jr6c0rlbZQFlmarSIlRaCjMWRzg3OIdWhynl\nQTBK0Wo3wW4uxLksZ6m80zOLUETgsT1VGb8WEeGxzmq83++CdzWU8eslSzgi8D/OjuBEa3nSqaYb\n8ZlDdSjQE17q0m5NwrYXBC1lGMm0VZoREcBImtWRN1QuCEC0PUAmKpbDEYGu4dzGD2SICCday3Em\ny3GEN2/MwG4uxKGG7HR4fayzCoFQBO/2qKdl9Ds9s5hYXMaz9zanfa5ykxGf6KzCLy9NIBDS5pyE\nbS8Icm50U7l2BEHOCOpLs6fRjaklVFoKYTcXKrGsjLCvzoYBpxc+hT9V3phcgmc1lLP6g3jua7Nj\nZmkVg1mKI6yGwnjn1iw+0VmVtQr1I83lKDcZVZVt9JMzI6gqLVxLjU2XLxxpwLwvgN/fUp9rLBlY\nEFw+1FqLUGxUX5bNRrQ5zNAR0DeTXhzhxqR6A8oy++utEAKKz6+V+wepwUIAgPvaous4M5Adt9GH\nA3PwBcJZcRfJ6HWEj++uxO9vzariE/TInA/v9jrxzLFGFCToaroVHmp3oLq0CL/QqNto2wvCoAa6\nnMZTVKBHY3lJWhZCIBTBgNOrancRcHvG8tXxRUXPe3ZwHk0VJWlPBlOKpooS1FqLsiYIb16fgcmo\nXxOibPFYZzU8KyFVVPX+j7MjMOgIzxxrVOyceh3h8/fU4Z2eWcwsrSh23myRlCAQ0eNE1ENE/UT0\nrXVeJyL6rvT6VSI6vNmxRPS3RHRL2v+XRHT3nLosMDynPUEAgB2VlrQshP5ZL4JhoXpBcFgKUWMt\nUrSFRSQicGF4Pif9izaCiHBvmx1nBucy3hMnEhF468YMHtlViUJDdi3jB9rtKDHqc+42WgmG8Yuu\ncXxyTzWqFB4b+4V7GhARwL9e1J6VsKkgEJEewPcAnATQCeAZIuqM2+0kgHbp6zkA30/i2LcA7BVC\n7AfQC+Av0343W2TBF8CiP4hWDQrCziozhly+lE1vOaCstpYV66F0xXLfrBfu5WDW211vxn1tFZj3\nBdAzk9lJcZfGFuHyruIxhfzmW6GoQI+Hdzrw1o2ZnDaDO31lEu7lIL6cRqrpRjTbTTjWUo6XusZz\n2rQwFZKxEI4B6BdCDAohAgB+BuBU3D6nAPxERDkLwEZENYmOFUK8KYSQI4VnAaRWIpgGaxlGGqlS\njqW9yoxQRGBkLrUg5M2pJRQV6DTR0G9/vRWDLp9is3nPD6uj/iCeeyX3zYcZdhu9eX0aBXrCx3ZV\nZvQ6G/HYnirMLK3iisJuwGQRQuCnZ0bQXmnOWFLBF480YMjlw/kctSRJlWQEoQ5AbPnduLQtmX2S\nORYAvg7g9fUuTkTPEVEXEXU5ncqmq8kZRlp0GbVLjch6U3Qb3ZhcQkd1KfQqmoGwEfvqo97E7gll\nAstdw/NwWArRqJKBQDK1tmK02E04M5C5GcRCCLxxfRonWitQmqX50fH8Tx1VMOgoZ0VqV8bduDbh\nxlfubcpYQd6n9tXAUmTAi+dHM3L+TJHzoDIRfRtACMA/rfe6EOIHQogjQogjDsfWuhBuxrDLBx1B\ndQ+GZGhzmEGUWuqpEAI3p5fQqdIK5Xhut8JW5hNl1/ACjjWXZ7w6NxVOtFbg3OA8QuHMZOH0z3ox\nPOfHYxsMj88G1pICnGitwJvXcxNH+OmZEZiMenz20HqfTZWhWDr/a93TWPAFMnYdpUlGECYAxA4X\nrZe2JbNPwmOJ6KsAngTwJZEDZ9vQnB/1ZSUwGnKui1um2ChlGqVgIUwvrWDRH1R9QFmm3GREna1Y\nkRYWE4vLmFhcxpHm7BRjbZX72irgWQ2hW+E0Wxn5U/kndmc/fhDLY3uqMOD0KT79bzPc/iBeuTqJ\nU4fqYMmwhfTMsUYEQhG8fEk7M5eTeRJeANBORC1EZATwNIDTcfucBvCslG10AoBbCDGV6FgiehzA\nXwD4tBAiJwNJh1xeTbqLZNorzSlZCDcmtRNQltlfb1Uk06hLih+oLaAsI89ZzlT66ZvXp3GwwZbz\ndFu5ECzb2Ua/ujyB1VAEf6pgqulG7K4pxaFGG148P6qZ4PKmgiAFfr8J4A0ANwH8QghxnYieJ6Ln\npd1eAzAIoB/ADwH8eaJjpWP+HoAFwFtEdJmIXlDubW2OEALDLj9aKrTnLpJpr7JgyOVDcIvuBbmH\n0S4NCcK+eitG5vxw+9MLLF8Ynoe50JDx7p6p4rAUoqPKgg8zEEeYci/jyrg7q8VoG1FjLcaBeive\n6M6eIAgh8OL5Ueyrs67Vt2SaZ441on/WiwvDC1m5Xrok5SsRQrwmhNgphGgTQvxnadsLQogXpO+F\nEOIb0uv7hBBdiY6Vtu8QQjQIIQ5KX8/ffeXM4fIG4F0NaSLLZiPaK80IhreeaXRjagmN5SWaGAgk\ns78uGli+mmYcoWt4AYcabTAoVJmaCe5tq8CF4XnFq3l/J7mLHuvMXfwglpP7anBl3I3xhew4CC6P\nLeLWtEfRQrTNeHJ/DSyF2gkuq/d/RYYZlh6iTRoWhJ1Sd8atxhFuTnk05S4ClGmF7fYH0TPjUa27\nSOa+tgqsBCO4PKZsWuabN2bQ6jCpZjreSWlK22+zZCW8eH4UJUY9Pn2wNivXA4ASowGfOVSHV69N\nYdGv/uDy9hUEKeVUK5PS1kPONNpK6qlvNYThOZ9mAsoy1uICtDpMaT0kL44uQAioNqAsc7y1AjqC\nom4jefaBUk3clKCpwoTOmlK8ngVBWFoJ4jdXpnDqYG3WLeO14PJF9QeXt60gjM77odcR6sqKc72U\nlCk26lFfVrylwPKtaQ+EgOqb2q3HwXobLo8tphygOz88D4OOstbuOVWsxQXYW2dVtEDtj73O6OwD\nFQkCADyxrxofjSxg2p3Zvj+/vjyJ5WA4q+4imc7aUhxssOGfNRBc3raCMDznR52tWLEuh7li5xZ7\nGt0eiqPOoGoiDjTY4PSsYjrFpmFdw/PYW2fVRGfbe9sqcGl0QbF50m/fnEG5yYiDKhNDeZbzb7un\nMnYNIQT++dwo9tSWrtW0ZJs/lYLLXSPqDi5r+2mYBiNzPjRpOMNIZkeVGYMub9KFTDemllBaZECd\nTXuW0YGGaGD5Sgpuo5VgGFfG3DiqcneRzL2tFQiGBbpG0m99EApH8E6vE490OFRXmd7mMKOjyoLX\nMug2ujruxs2pJTxzrDFnxYhPHpCCy+fUHVzexoLg12QPo3h2VloQDAsMJzk97ebUEnbXlKqySncz\ndtdYUKAnXB7bemC5e8KNQDiCIyoPKMscbS6HQUeK1CNcHF3Eoj+Ij+e4GG0jTu6rxoXhecx6MuM2\nevH8KIoL9DiVxWByPHJw+RWVB5e3pSAs+gNwLwfzwkJor4pmjPQnEUcIRwRuTXk0F1CWKTTo0VlT\nmpKFIDe0O9KkDQvBVGjAwQabInGEt2/OoEBPeLDdrsDKlOfk3hoIAbxxXfneRp6VIE5fmcRTB2oy\nXpm8GVoILm9LQZA/TTflgYUgpxAmk2k0MufDcjCsyYCyzIEGG65NuBHeYuvkruEFtDlMqFDxuNB4\n7murwNXxRSyl2eX17VuzON5SkfMH4kbsrDKj1WHKSBzh9JVJ+AO5CSbHo4Xg8rYUhJG1ttfatxBK\njAYp02hzQbg5FbUidldrWBDqbfCuhjDoTD6QHokIdA3Pq77+IJ572+yICODcYOpxhJG5aL+gR3fn\nptV1MhARnthbg7OD85jzrip67hfPj2JXtQUHG3Iyf+suvnyiCf2zXpxRwcS49dimghC1EBo02OV0\nPXZWWdCXxFCVnukl6Oi2m0mLyIHlrdQj9M16sbQS0pwgHG6yobhAjw/6U69HePvmLADg0V3qjB/I\nnNxXjbA0yU0puifc6J7IbTA5nif318BWUoCfnhnJ9VLWZVsKwvCcDzXWIhQVqD/9MBnaK80YdPo2\nzTS6Oe1Bi92k6ffdajfBUmjY0nCV8ypvaLcRhQY9jrWU472+1OeAvH1rBu2VZjSq3BrurClFU0WJ\notlGL3WNwWjQ4TMHM9fmeqsUFejxb4404M0bM5hyL+d6OXexLQVhZM6fFwFlmfYqCwLhCEbmE2ca\n9Ux7sEvD7iIA0OkI+xusuLKFTKOu4XlUWgrRUK69VNsH2+0YcPpSengsrQRxbnAej6o0uygWIsLj\ne6vxYb9LkSyclWAYv7o8icc6q2AtUVfs5MsnmhARQpUpqNtXEMq1H1CWaZcCy4kK1HyrIYzO+1Xb\n5XMrHKi34ebUElaCyRVtdQ0v4KhKB+JsxgNSZtB7fVt3G73X60IoIlQdP4jlib01CCnkNvrdzRm4\nl4P44pGGzXfOMg3lJfhYRyVevDCmeAPDdNl2guBdDcHlXUWTPX8sBDnTKFHqqTy4vSMfBKHBhlBE\n4MbU5kNk5IE4WilIi6ejygK7uTClOMLbN2dgKynA4UZtvPf99VbU2YoV6W30Utc4aqxFuH+HOlNt\nv3KiCU7PKt7I0dS4jdh2gnA7wyh/LARTYbTyOFHqac90VBC07jICsJYxkkw9gjwQRysFafEQER7Y\nUYEP+l2IbCHVNhwR+EPPLD7WUam66uSNICKc3FuN9/qcaaXaTrmX8V6fE39yT71q3/vDOx1oLC9R\nXXB5GwpC1M+uxTnKiWivMidMPb01tQST1AxP61SVFqG6tCgpQfhoZAEmo17TrrIH2h1weQO4NZ18\nE8NLowtY8Ac14y6SObmvBsGwwFtpFKm9fHECEQH8yT31Cq5MWXQ6wpdPNOL88DxuTWdmXGoqbFtB\nyKegMhBNPR1wejcs2Lo17cHOagt0Kv3EtFUONFhxJYnZCBdHF3BQ5QNxNuMBye3xfn/y2Ua/uzkL\ng47w0E5HppaVEQ412FBnK8YrVydTOl4IgZe6xnC8pVz1hadfuKcBhQYdfqIiK0G7/0tSZGTOB7vZ\nqNqqzVTZUWlGIBTB6DqZRkII9MxoP8MolgMNNgy5fAkzUnyrIdyc8mjGh74R1dYi7Kg04/3+5IuZ\nfn9rBsdaylGqsb9znY7wqf01eK8vtWyjC8MLGJ7z4wsqDCbHU2Yy4qkDtfjVpYm0q9GVYtsJwvCc\nL+/cRcDt6Wm96xSozSytYtEf1LTbJJ6D9dJIzQRWwpXxRYQjAoc10r8oEQ/ssOP80FxSmVVj8370\nzng1kW66Hk/tr0UoIlKapPZS1xhMRj2e2KeOMaGb8ey9TfAHwnj5o/FcLwXANhSE0TzpchrP7Uyj\nu+MIso8ynwRhb70VRIkDyxel3vOHVTYDIBUebLdjJRhZe0+JePtm1P/+6C5txQ9k9tZFi9Reubq1\n3ka+1RBevTaFJ/fXosSojXnh++ttOFBvxU/Pjqiiv9G2EoSVYBiT7hXV+xZTwbyWaXS3hXArjzKM\nZEqLCtDmMCesWL44uoj2SrPqCpNS4XhrBQw6wvtJpJ/+oceJVrsJzRqdF05EeGp/LT4ccMHpSb63\n0avXpuAPhPHFo+oNJq/HV+5txoDTp+iEvFTZVoIwJvnXm/OoBiGW9irzuqmnPdMeVJcW5cWDMZYD\n9TZcHnOv+8kqEhG4OLqg+fiBjLnQgEONtk0FYTkQxpnBOTzSoU3rQObJAzWIiK1NUnupawytDpPm\nfudP7q9BucmIH38wnOulbC9BGM7TlFOZjioLBmbvnp52a9qDXRocmbkZBxuscHlXMbnOPN5Blw+L\n/iDuyYP4gcwDOxy4NuHGgm/jYOvZwTkEQhE80qGt7KJ4OqosaK804zdXkhOEQacXF4YX8IV7GjRX\nkV5UoMeXjjfi7Vsza3VSuWJbCUI+FqXFslPqaRQ7PS0YjqB/1pMXFcrxJBqpuRY/yCdBaLdDCCR0\nLfyhZxbFBdGmeFqGiPDk/lpcGJlPqo/Tv14ch46Azx1WTyO7rfDlE03QE+EfPhzO6Tq2mSD4UVpk\ngC3PXCcy8kM/No4w5PIhGBaanoGwEbuqS2HU69YXhNEF2EoK0KpRP/p6HKi3wlJo2NBtJITAOz1O\n3NdWoemOtjJPHohOUnt1k+ByJCLwq0uTeLDdgarSoiytTlmqSovw5P4avNQ1Dk8OU1C3lSAMz/nQ\nVGHSnEmZLDsqzSC63aYCiM5QBvKjh1E8RoMOnbWluDR6tyB8NLKAQw22vCnEAwCDXocTbRUbFqgN\nunwYnffjEY1mF8XT5jCjs6Z002yjc0PzmFhc1qx1IPO1+1vgXQ3hpa7cpaBuK0EYnc+vttfxFBXo\n0VxhusNC6Jn2wKAjtDm0OxQnEYcaoyM1Y+Mmbn8QfbPevIofyDzYbsfY/PK6vuZ3eqJC8YjGqpMT\n8dSBWlweW1xLCFmPly+Ow1xowGOd2qg92IgDDTbc01SGf/hweMsjYpVi2whCMBzB+MJy3sYPZHZW\nmdc6mwJRQWhzmGE05Oev+lBjGZaD4Tve88Wx/IsfyMhtLNZrh/1OzyzaHKa8mQQIRDNwAGxoJSwH\nwni9exqP761GsVH7brKv39+C0Xk/fn9rNifXz8+nxDpMLCwjHBGqnxyVLh1VFgy7fGsVrbem8zOg\nLHNICizHuo0ujSxAryMcqFfHHF0labGbUGcrxvtxguAPhHBucB4f03i6aTwN5SU42GDDb66s39vo\nrZsz8K6GNO8ukvnknirUWovwo/eHcnL9bSMIw3meYSTTXmVBRAADTi+WVoKYWFzOy5RTmfqyYtjN\nxjsE4aPRBeyqtsBUqI1q1a1ARHiw3Y4PBlx3uMnODMwhEI5ovv5gPZ46UIsbU0sYcN5dY/PyxXHU\nWotwoqUiBytTHoNeh2fva8aZwbm1+F822TaCIDd9a853C0GyBvpmvDEzEPJXEIgIBxvKcElyE4XC\nEVweXczL+IHMQzsd8KyEcDkmu+oPPbMoMepxtCX/3ven9tWACHglribB6VnFe30ufOZQXV4lDzx9\ntAFFBTr8+IPsWwnbRhCGXX4UF+jhsBTmeikZpbnChAI9oWfGs9ayoiMPU05jOdRow6DTB7c/iJ4Z\nD3yBcF4Lwv1tdugI+GNvNIh8O93UjkKD9v3o8VRbi3C0uRynr0zcUZV++sokwhGRN+4iGVuJEZ8/\nXI9fXZ7EnDf51h1KsG0EYWTOh6aKkrxNOZUxGnRotZvRO+1Bz/QSLEUG1Fq1mZudLHIc4fL44u2C\nNI21L9gK1pICHGyw4V0pjjDg9GJ8YVnz1cmJ+PSBWgw4fXeMTX354jj21VmxozL/LOCv3d+MQCiC\nfz43mtXrbh9ByPOU01h2VluiFsKUB7uqLXkvgvsbbCCKTgm7OLoIh6UwLybDJeLBdgeuji9iwRe4\nnW6ax4LwqX01MOgIv74cDS73znhwfXIp76wDmR2VFjy004Gfnh1BIBTZ/ACF2BaCEI6IvG17vR4d\nVWaMLyzj4uhCXnU43QhzoQEdVRZcGl3ERyMLuKexLO9F8KGdDggBvN/vwh96ZtFeaUZ9Wf5+4Ckz\nGfHwTgdOX55EJCLw8sUJ6HWEpw7U5nppGePr9zdj1rO6YYZVJkhKEIjocSLqIaJ+IvrWOq8TEX1X\nev0qER3e7Fgi+gIRXSeiCBEdUebtrM/00goC4Ujep5zKyMNyIiI/K5TX41CjDe/2OjE678/r+IHM\ngXorSosM+G33NC4MLeS1dSBz6lAdppdWcHZwDr+6NIGHdzpgN+dvTPDhnQ50VFnww/cGszYrYVNB\nICI9gO8BOAmgE8AzRNQZt9tJAO3S13MAvp/Esd0APgfgj+m/jcSMuLZHyqlMrAjszuOU01gOxQzB\nOdyUf/UH8Rj0OjzQbser16YQCEfyrv5gPT6+uxIlRj3+8pfXML20krfuIhkiwr99sAW3pj1JzcFQ\ngmQshGMA+oUQg0KIAICfATgVt88pAD8RUc4CsBFRTaJjhRA3hRA9ir2TBIxIKafbJYbQEOM6kK2F\nfOdg420R2FNrzeFKssdD7betgiPN2u5umgwlRgMe66zCyJwfhQYdPq7REaFb4dTBWjgshfjhe9lJ\nQU1GEOoAjMX8PC5tS2afZI7NOMNzPhToCTXW/A40ysTmZFs0NmQ9VXbE9GrKh06fyfCQ1LOoQE95\n25oknlMHo4+PPbWl2+L3XGjQ48/ubcIfe513NK3MFKov5SSi5xB1Q6GxsTGlc7RUmPDZQ3XQ51Hx\nymb8v88egS8QyvUysoZOR/ibz+9HVZ6n2MZSayvG//74Ltzblh9VusnwYLsd/+7hVjxzNLVngRb5\n0vEmnBuaRzCc+Wwj2ixYQUT3AviOEOKT0s9/CQBCiP8rZp//DuAdIcSL0s89AB4B0JzEse8A+F+F\nEF2bLfbIkSOiq2vT3RiGYZgYiOgjIcSmyTvJ2JkXALQTUQsRGQE8DeB03D6nATwrZRudAOAWQkwl\neSzDMAyjAjZ1GQkhQkT0TQBvANAD+JEQ4joRPS+9/gKA1wA8AaAfgB/A1xIdCwBE9FkA/w2AA8Cr\nRHRZtiQYhmGY7LOpy0hNsMuIYRhm6yjpMmIYhmG2ASwIDMMwDAAWBIZhGEaCBYFhGIYBwILAMAzD\nSGgqy4iInABGUjzcDiA7HaK2Bq9ra/C6tgava2uodV1AemtrEkJs2hJXU4KQDkTUlUzaVbbhdW0N\nXtfW4HVtDbWuC8jO2thlxDAMwwBgQWAYhmEktpMg/CDXC9gAXtfW4HVtDV7X1lDruoAsrG3bxBAY\nhmGYxGwnC4FhGIZJwLYQBCJ6nIh6iKifiL6V4Ws1ENEfiOgGEV0nov8gbf8OEU0Q0WXp64mYY/5S\nWlsPEX0yZvs9RHRNeu27RJTWhB8iGpbOd5mIuqRt5UT0FhH1Sf+Wxeyf8XURUUfMPblMREtE9B9z\ndb+I6EdENEtE3THbFLtHRFRIRD+Xtp8jouY01vW3RHSLiK4S0S+JyCZtbyai5Zh790KW16XY707h\ndf08Zk3DRHQ5m/eLNn425Pzvaw0hRF5/Idp2ewBAKwAjgCsAOjN4vRoAh6XvLQB6AXQC+A6ig4Di\n9++U1lQIoEVaq1567TyAEwAIwOsATqa5tmEA9rhtfwPgW9L33wLw19leV9zvahpAU67uF4CHABwG\n0J2JewTgzwG8IH3/NICfp7GuxwAYpO//OmZdzbH7xZ0nG+tS7Hen5LriXv87AH+VzfuFjZ8NOf/7\nkr+2g4VwDEC/EGJQCBEA8DMApzJ1MSHElBDiovS9B8BNJJ4jfQrAz4QQq0KIIURnShwjohoApUKI\nsyL62/0JgM9kYMmnAPyj9P0/xlwjF+t6FMCAECJR8WFG1yWE+COA+XWuqdQ9ij3XvwB4NBlLZr11\nCSHeFELIc1LPAqhPdI5srSsBOb1fMtLxXwTwYqJzKL2uBM+GnP99yWwHQagDMBbz8zgSP6AVQzLX\nDtcAkw8AAAMDSURBVAE4J23695J5/6MYs3Cj9dVJ38dvTwcB4HdE9BFFZ1UDQJWITrcDop/Oq3Kw\nLpmnced/0lzfLxkl79HaMdLD3A1AiaHIX0f0k6JMi+T+eJeIHoy5drbWpdTvLhP360EAM0KIvpht\nWb1fcc8G1fx9bQdByAlEZAbwrwD+oxBiCcD3EXVbHQQwhajJmm0eEEIcBHASwDeI6KHYF6VPGzlJ\nO6PoiNVPA3hJ2qSG+3UXubxHG0FE3wYQAvBP0qYpAI3S7/p/BvDPRFSaxSWp8ncXwzO484NHVu/X\nOs+GNXL997UdBGECQEPMz/XStoxBRAWI/sL/SQjxMgAIIWaEEGEhRATADxF1ZSVa3wTudAGkvW4h\nxIT07yyAX0prmJFMUNlEns32uiROArgohJiR1pjz+xWDkvdo7RgiMgCwAphLdWFE9FUATwL4kvQw\ngeRimJO+/whR3/PObK1L4d+d0vfLAOBzAH4es96s3a/1ng1Q0d/XdhCECwDaiahF+hT6NIDTmbqY\n5K/7/wDcFEL8l5jtNTG7fRaAnP1wGsDTUnZAC4B2AOclE3KJiE5I53wWwK/TWJeJiCzy94gGJLul\n6/+ZtNufxVwjK+uK4Y5Pbbm+X3EoeY9iz/UnAH4vP8i3ChE9DuAvAHxaCOGP2e4gIr30fau0rsEs\nrkvJ351i65L4OIBbQog1l0u27tdGzwao6e9rKxForX4BeALRiP4AgG9n+FoPIGryXQVwWfp6AsBP\nAVyTtp8GUBNzzLeltfUgJjMGwBFE/zMNAPh7SIWEKa6rFdGMhSsArsv3AVH/4tsA+gD8DkB5Ntcl\nnc+E6KcYa8y2nNwvREVpCkAQUd/sv1XyHgEoQtQt1o9opkhrGuvqR9RfLP+dydkln5d+x5cBXATw\nVJbXpdjvTsl1Sdv/AcDzcftm5X5h42dDzv++5C+uVGYYhmEAbA+XEcMwDJMELAgMwzAMABYEhmEY\nRoIFgWEYhgHAgsAwDMNIsCAwDMMwAFgQGIZhGAkWBIZhGAYA8P8Dclor2wHG32sAAAAASUVORK5C\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef2da0ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular._reset(new_base_lr=0.003, new_max_lr=0.009)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef26f77f0>"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef2f9bb38>]"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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HnJocrI5+WbRqNrrYO4Xf5+HAJmVwnMaKINQAvTHP+4xjVsZsOFdEngf6lVKX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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef38eb390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr = lambda x: 0.5*(1+np.sin(x*np.pi/2.))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(scale_fn=clr, scale_mode='cycle')\n",
    "\n",
    "model.compile(optimizer=RMSprop(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef3259048>"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=40, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcefa3a7c50>]"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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dsw59Hy4y1RNDCC9wx6J2bpM7FrlL4krQU423UupJGIO+/bVHbT8rAO/1eq75\nuquLKE46vb7rzDQIhmxuuNl7Y3kNZ0xROyeDMv81vPHEfKjPSRJGPv7+mSOw1wgGvWYdOkbMIHkg\neD8rpXCp1cW5U1XXv9drZaxvGfo+bhODNMKxMbcVAmBc8xcvtbG7qzDjcu97/QxAUz+XBgJ3xwrB\n+mBYzITRmW6rk6muVO5oELZj5jVkJrilXzKs75Mld8LOrsKLK72h12w3gkHROVDMl8JXsVqidsNm\ny5qCrEnC2vBpxDWzEQyKDmE7Rkca+bDEAWapVsKL17qJE7mbWoOgS9iOCbuxxrDCHSafm8Gpo8VM\nZaC80umhv7M79Jp1GEFdelXAQOAuTAzByk0fMlt+fQaLEK0NnxaiM4I6hO0YazOkEM9zY7k7NDYG\nGIZia0clTuRuag2CzoECMGagYXzLbqJ2TnTq+ySBwbLafaCwfK0hjCAP3jqCjSxwF6afm0Py8Zna\noQM4dGA2W/28slfUzsnrNdRfGMJ2hVDCdoyObXGbK3tF7ZxwplHSVvxTbBD0uRKA8CuEhpWP7z5Q\n8N+SrKXuF6c+vhtLC+GybnSmIwJGHCFsP9tF7Zywvk+WXEaN5TWcOeoeGwMMI1g+MBvKNWgI2+lb\n7fN7BqWx3N1XW2OHRe6StuKfWoMwSFPTF0MII3DHg6MzN91OvVZKtJa6X9xE7ZzUF0t4cSW4yJ0u\nYTtmvpgPVbTkJmrnJGtFiMa2mcPva6PwMtw+2jqE7ZiwAnfODZ/cqJQKqJYKskJICtZAoXlWEVTg\nrtnq4pbDe0XtnGRN5M5Nt8nJYEORXqDP6HT7OHIwH1rYjgkrcGffKnQY9cUyrl7fwNpmeH2fSePc\n8GkYYff86PT0VKMDQG6GQgncOTd8GsbSQklWCEmhrWEXLTuVkJkJRlXjmMFRo+BbEmg4tOLdsDYU\nCehCafe2tLkSgHDbpa73d3BldX3kzBEYaN9cyoDbyEtsDDDu7VevbwQWuWt39RSZMmFcg42V0XEi\npl5LXhHi1BoEnfnp9vcJchMZG66PXlYDhh98oVzIhH/5+voWVtY2h6YiMpavNaAR7HT1uRIAFj7b\nClQ4xgJuYwfHxfBB1qTgJTYGDAbPICJ3OoXtmDBp5FayxJjJzlKtZIjcadh7QRfTaxA0CdsxA4E7\n/zfRtSGidm5kJdPIyrYZ89CEFbnT6UoABgJ3NwMI3HkJogPAqaNFzFC4+oukMFA5HT84Gsf772ed\nwnZMmEKBiyZ3AAAfR0lEQVTTxhBROyeWom+CDP/UGgRdwnbMQODO/000rqrRji59n0kzLuXUTpgg\nqy5hOyaMkGGz5S5q5+TAbA4nq8XM9HPt0OjYGDAQuQui76M7kwwIl0butuGTG0ksQpxag6BL2I4J\n4zIaJWrnpF4ro93ta9vzdVI0V9YwO0M4dXS8dEiYNExdwnZMGIG7RmsNx+bdRe2cZGklOC64CgxE\n7oIYQZ3CdgwL3AXZ+8K5VegwWOQuSf08tQZBl7AdwwJ3QQbqRmsNB2ZncMyDdk1WNlFpLHdxslpE\n3kP2T90UufO7oYhOYTumEiJHvbmy5mlFBBgrwUsrXS17Sk+KwYZPXq85mNy5TmE7xhK42/IncDds\nwyc3WH0gSaqnU2sQOpqDUACnJAZzGZ1ZKHkS9hro+yRnmRkEP4Nj0A1F2K2jM4ZQLQZzDXLigJfZ\nMmAMjpvbu3h1Nb01J8M2fBrG0oIh+OY3YK+7psh4r2CbXg3b8GkYSwkTuZtag9DWKGzHVErBMhMa\nHvLxmeOVIgq5mUQFovwyELXz+tAE87W2o/AtBxS4e+3GBnr9Hd9GMEnuBL+M2vDJjaAid4OaIr0r\nBMB/P4+TJnFSr5UTJXI3lQZha2cXNze2ta8QgmzO3d/excuddc8PTW6GcCaBBS1+GCdq5+RkQF+r\ntULQaPjLAQXurJnjmIAyk+RdtbxixcbG1NcwQff8aHf1CdsxlYACd83WaFE7J0u1UqJE7qbSIFg+\nR41BKCDY1ntcuON1hQBwkDXNM0fvQXRgIHLnd6DoWAKG+vqZBe78zhytax5Td8FUSwXMF/MpXyGs\njRS1cxK08LLT0ydsxwQVuGu01oZu+ORGPWErwak0CLqL0phqgIHi4rK/ZTVg3EQvtXvYSsgy0y9+\nUk6ZIKmnUaQjAkYcwe9A0TRF7RYPuYvaOSEiLC2k2/A3W92RonZOWOnVd6xIo7AdE1TgzkuBqZ16\nwlJPp9MgRBCEAgYCd34G6qbHMnc79cUStncVLl8Lpu8zaRqtLioeCnfsLNVKuHzNn8idFUPQJGzH\nBBG4420z/cxiDSOYjIEiCM2VriU94gVWevV7zW2NwnZMEIE7FrXzs9qfLxoid7JCmCC6he0YS+DO\nx03UWDZE7coHvPs/w8o5TBpW/PRDEJG71Z5eYTumWioEiiGMq8p2Ul8so3XTf7ptErA2fPIYP2CW\nAqSermquRgcGAnd+VggsaudnhQAYqwRZIUwQ3cJ2DLug/FQ4NlfGi9o5WQroa00KftIvGZ5p+rnm\ndm9Lex8D8L1JjldROyf1gOm2ScCKjflYIQDBRO4MYTv9/ezXNehV1M5J2D0/dDKVBiHKGALgPTPB\nyk33+dAcmsvjlsMHEjOr8AOL2gV5aAB/vlZDtkLvKhDggcK7wN24/XWHkURpA69YsbEAKwTA+zUr\npcyaIv397FfZ1toq1K/hX0yOyN10GoRuH8WCPmE7hgcfrzcRi9r5fWgA40FL4wrBq6idE95QxNcK\noavflQAY/exH4M6PVpWdoOm2SWAQG/O7QuBKfG8G4cbGNnY0C9sxlWLel8Bdc2X8hk9uWC7gBKwS\nptIgtCOoUgb8C9xZuekeUxHt1BdLaCyvBdJamSRhrnlpwV/AcTWCYCPgX+Cu0VrzJGrnhKUNUmkQ\nWl0sehC1c3LqaBHkQ+lV91a4dvwK3DWWvReY2hmoD0y+n6fSIBga+REsMX0K3DUCzpYBYyZ1Y2Mb\n11ImctdoGaJ2Xgt37PjVumlH6Erg9/dCs9X1LGrnJGnSBl4xEgf839dz+RxOVIqeVwj8rEXxPFd9\nCtw1V/wnDgCGyF0+R6G2ENXFdBoEs5BFN34F7po+RO2cWAUtCZhV+KHZ6uLkUW+idk6sDUU8ZN1E\nIWzH+JU18CNN4iRp0gZeGOg2BbvmpVrJ830dVTwQMFJCvQrcsahdkJVvPjeDk9VkiNxNqUGIxmUE\n+EtJbPgQtXMSZkORSeJlq9Bh+BG5i0LYjqn6WAkqpXBpzCbzo6ib0gYvJ0TawAtWbCyoQVgo49KK\nN5G7TkQZg8Z7GqsOL/3sdZe0YSSl5mQqDUIUwnZMpZT3XIfgZZP5Ydx25CDm8jOJmFV4ZXtnF5ev\n9XxnVTF+9H0GroQo0k6NgcJLP/sVtXMSVOl1kvhV/HRSX/QucmetECJcCXrpZ7+idk6WamVcTsBK\ncOoMQlTCdoxXgbvN7R283FkP/NDMzFDqMo1e6ayjv7PrWezMCW8o4meFEEU/+xG4YxHCwINjCmtO\n/GpVOfFTeNnu9jE7Qzjko7DTK34E7jg25mXDJzeSshKcOoOwGoHgmR2vAncvmTIMQWcUAAKV+U+S\noKmIjJ+smyiE7Rg/AndBaxCY+WIBC+VCqtRtm6ao3W0BYmPAoAjRSzC909vCvGZhO8aPwF2z5X3D\nJzeSshKcOoMQhXa6Ha8Cdw1rWR3cINRrZbzc6WHD565Ok6Kp4Zq9Zt1wH0QWK/Jo+BvLaygfmPUs\naudG2rbTZJkOr6J2TmplQ+TOk+Hv6t0i1Y4fgbsgcix2krISnDqDEMXuSnYqxYIngTvu+DMBZ8uA\nkcuvFFIjctdoraFSzIfy9y7VSp6ybrifj2gWtmMqJW8Cd00zoBxmBluvlRKRkuiVoCmnDIvceTH8\n7V4/ssmdV4E7vxs+uTFfLOBoqTDxFGNPBoGI7iaiC0R0kYgecvk7EdHD5t+fI6I7xp1LRL9GRF83\nj/8TIprXc0mjibKQBfAecGy2/IvaOeGMhknPKrzidfPxUdRrZU8binQiErZjKkVv2WSN5bXAmSdM\nvVZGu9v3vVnLJBjExsL3s6dYUUTV6IB3gTu/Gz4Nw6sRjJKxTwsR5QB8FMA9AG4H8A4iut1x2D0A\nzpr/HgDwiIdzPwvgO5VSbwDwDQAfCH01HuBS9CgKWQDvfsfmSvAMIyZJFY5eaIacOQI2/fgxZf6d\niITtGC8xhF5/G69e39AyOAKT9y97YRAbCz84ehG56/SiEbZjqh4Mvw5XKJ8/6cmdl+nTnQAuKqWa\nSqk+gMcB3Oc45j4An1AGTwGYJ6JbR52rlPqMUop7+ykAxzVcz1iizD4BvPkdlVLGzDHkQ1MszOLY\n/MFUuBMMUbt+KD8rYMtAGRNkjUrYjqkWC1hdHy1wd2nF/0ZAbqRJ5M7aRzlgJhnjZTvNKIXtGC/K\nto2QKafMUq2Ea92+L7kM3XgxCMcAvGz7/RXzNS/HeDkXAP4ZgD9z+3AieoCIzhPR+Var5aG5o4lK\n2I7xInB3rdvHjY3t0DMKgDONkj9zbIZMRWRY5G7cCiEqYTvGi8CdlTgQsO6COV4popCbSUc/h8wk\nY3hwHXXNUQrbMV4E7oJs+OTGYDvNyRn+iQeVieiDALYBfNLt70qpjymlzimlztVqtdCfF5WwHTOQ\nwB5+E7GLJ+yMAjCXmSkQubNmjiEHCsBwG41bIUQlbMdUPegZNU1Ru9NHw11zboZwZiEdhr+xHEzU\nzsmpo0XM0OgVQtTxQH7vca7BZsgMIyYJqadeDMIVACdsvx83X/NyzMhzieifAvhhAD+pYhrRohK2\nY7zEENjFEzbYCBiDY7e/g+Wbm6HfK0qaIUTtnHjZUKTdi64aHRgULY3q50YIUTsnSQg4ekFHbAww\ndMGOV0bXnESdMcjv3emNFrhrBNgNz40TlYMTF7nzYhCeBnCWiM4QUQHA/QCecBzzBIB3mtlGdwG4\nrpS6OupcIrobwM8D+BGlVGx5k1EJ2zFz+RyKhdECd2FE7ZxYS+uEB5YbrbXAonZOLJG7IZlcLGwX\ndQwBGB0rCiNN4qReK+Nyu4f+dnJF7nTFxphxRjCqrXDtVEqjBe54w6cgonZOZnMzOHXUu7BfFIx9\nOs3A7/sAfBrA1wD8gVLqBSJ6kIgeNA97EkATwEUAHwfwnlHnmuf8JoBDAD5LRM8S0aP6Lms4nYhn\njsD4lMQwonZO6h58rUkgjPqlE+uah6wS2hEK2zHjpM53dw3FT12DY32xhJ1dhZfayV0l6IyNAUY/\njxK5i2orXDscsB7Wz0E3fBrG0sJka048JcErpZ6EMejbX3vU9rMC8F6v55qvv95XSzXR7kYbQwC4\naGn0zPE7jh3R8lm3HD6AUiGXaAmL7Z1dvHiti7d++6KW97Nn3dxxsrLv750Ihe0YdjsOcxm9dmMD\n61s7+o1gq4vXLx7S8p66GcTG9K0Q1rd2cPXGhutqejVCYTtmIHW+heP7b7VQGz65UV8s4y8vLGN7\nZzeyGppRTDyoHCdRC9sxFXPPXTc2t3fwUruHuqYZBRGhvjj5/OVRvNJZx9aOCixq54Q3FBl2zVGn\nFgOGwF0+R0P7Oei2mcM4k4IiRJ7Z6jaCw4KsUQrbMeN2x2uu6IuNAcYKYZIid1NlEKIWtmNGCdy9\ndK2HXaVvRgGYy8wErxAsgbeQ6ZfMuA1FBsHG6PqZiDA/IgOFB+7XaxocD83lccvhA4kWuePYWFBR\nOyfjCi87pmxFFMJ2zPyYJJHGcvANn9zgcWFSmUZTZRCiFrZjeOs9NwbbZuozCPVaGVdW18dWdU4K\nHsR0XvPSiA1F2PBHvRKsjpA6b7YMUbtaCFE7J0moZB0Fx8aCito5YZG7YT71Tncr8slddYwEdnMl\n+IZPbtR9SH9HwVQZhDjS1ABjILo5ROCOB7EwonZOeFZxKaEVy82VNVRLBa2+3vqIDUXa3T6IohO2\nY0ZthtRohRe1c2Jk3SS35kRnVhVgitwtDle3jbqmCBgI3Lm5BnWI2u37vGJ+oiJ3U2UQ4ihkAQau\nCrfBotnq4nWH50KJ2jlJ+naajWU9edp2lkZsKNLp9XF4LjphO2bUdqm6B0fAMII3NraxspY8kTuO\njemKmTD1EQV5nRgSRHIzhPkhAncsahdFP8sKIQbiSFMDRvsdw0oDu3H6aAlEya1FaK7ov+ZRAcco\nt0i1MyyGwKJ2uo1gklOMOTamvZ8Xy7h6fQPdzf3u0E7E1ejMsDRy3YkDzCSLEKfKIMRRyAIMF7hT\nSkUyc5zL53CiUkykyN31niFqp38WNVzwbbW3FangGTNM4E53KiKTZJE7HRs+ucFG1ekONYTtoo8h\nAMMF7sJuFTqMeq08MZG7qTII7YiF7Zhh8hUra0bhju4ZBWCK3CVwhdBY0afbZGe+aIjcuc2W46g1\nAYyBwk3gzpIm0dzPtx05iLl8MkXurA2ftLsG3VdFLGwXSz8XC67aZCxqp3uVMkkX8FQZhE4MQShg\nULTkvImsqkbNgyNgbiiysjZSjnkSDLTi9RvB+pCldXyuBLOfHYa/saxH1M7JzAxhaSGZmUa84VNY\nUTsnLHLnHByj3iLVTqXoHkMIu23mMCYpcjddBiFiYTtm2AphULgTxeBYxsbWLq7e2ND+3mFomKJ2\nJzQV7tgZNjjGIU8CDCpknSmJzZUujlf0iNo5SarIXaOlN/2SYZE75+DIz1Yc/czJA87sLkOORf+z\nzCJ3skKImHbEwnbMMIG7xvIa5vIzuO2InsIdO0ndPa3ZWsMpjYU7duqL+zcUYWG7OPqZtZKcvl5j\n20z9gyNgGP6XOz1sDBFbmwRWbExT4aETt5VgJwbZCqZSKqDvELhjUbsoVggscicrhIhZjWnmCLhn\nJjRXujizUNYiauckqRkoRj5+NIOjtXuabbBoW6nF8a0E7SuE3V2FSyv6hPyc1BfLUAp48VpyVglW\nbCwiI7jk4g61tsKNpZ/3C9zp2vBpGPUJbXw1VQYhrmAj4C5wF0XKKbNQLuDw3Gyi3AnbO7u4fE2f\n4qcTtzL/OITtGDeBOxa1i+yaE5hpNIiNRXXN+92hcQjbMXaBOyaqlFNmqVbGS+2ea+FllEyNQYhL\n2I5xCtxtbu/g5XYvshkFEZlyDslZIViidhFds9uGInH6lt0E7qJKRWQskbsEuQZ1i9o5cXOHxiFs\nx7gJ3HFsTJeonZN6rTwRkbupMQhxCdsxvNMSY4naRTSjAJKndTMYHKO55llT5M45UADxuBKIaN8W\ni1FmVQFAsTCLY/MHk9XPy/o2fHJjUH9hWwnGIGzHuO2O12zpFbVzMqmY4NQYhDiDUADnLu+dUQB6\nBd6c1BdL+NaNTdzcGL0peFxYy+oor7lW3rtCiDEdkT/H2c+6Re2cLNVKiZIpMWJjejZ8cqNWPoBD\nc3tF7oxq9Hgmd26xoqiyqhgWuRu3VaxupsYgtCcwUNgF7nRuMj8MXrInReSu0dIvaudkySFy1+lt\nxSJsx1RK+X0zx7pmUTsn9Vo5USJ3jQiq7+24uUOj3grXjiVwZ44hRmysF1lWFWCI3C2UC7HLnU+N\nQYh75ugUuGu01vC6w3MoRejzrFsVjslwJzQ1bT4+irpD5C4uYTvGcA3ujSFElVXF1GsldPs7+NaN\nzUg/xwscG4tyogPsTz2NQ9iOsQTuzH5+pbNuiNpFuEIAjJW1rBAiotOLR9iOcQrcNVvdSGcUAHCy\namjRJ2UTleZKtDNHwCZtYPpa4xK2Y+wCd73+Nq5e34g0TgQkK8V4EBuL2gjuFbmLqxqdsaeR697w\naRj1xfiLEKfIIMQjbMfYN9ZQSkXucwSAwuwMTlWLsc8q3GBRuzhmjsDgIY1L2I6pmrvj7e4qWypi\nPEZwUrtq2WlEnHLK2EXu4hS2YyqlgeGPIzbG7x+3yN3UGIS4hO2Yiq2KdWWtj5sRido5MUTuJr9C\nYFG7qGeO88XCng1F4l4hVEoF7Crg5sZ2bIPjLYcPoFTIJSKw3IjJCHLNSaO1FquwHWNPI2+01iIR\ntXPCK5A4+3lqDEJcwnbMYIWwFXlVo516rYxL17rYmbDIHbtwYjOC5nfM6YhxwbPUdq+PZqsbiaid\nEyJCfTEZKcaN1hpuOXxA64ZPbthF7uKOBwJGP/PnNlrRVaLbWZrAdprTYxBiErZj2DXV6fVjyTBi\n6rUy+tu7uBJzQYuT5koX+Vw0onZOjKybyawQ5m0piY3WWmSidk7s1zxJmjENjgdmczhRNUTu2jEW\nHzIcQ2Ddpjie5eNceCkrBP3EJWzH2AXumq3oRO2cLCUk06ixvIaT1egKd+ws1QyRu6vX17G5HY+w\nHWMXuItrcAQMn/qV1XX0+vt3EosLKzYWw+AIGNfcaHVjla1gWODutRsbkWz45MZsbganj8araTQ1\nBqET88wRGMwqGq21yETtnCQlA6W5Ep2onRO+5vMvdgDEU6XM8D11ba1vbBUacaCRGeg4TW6VYMXG\n4rrmWhmXVtasPaXjTh4ABvdYXPe2IXcuBkE7cccQgIHAXXMlGt1098/kncQmN1CwqF1ss2Xzc565\nbBqEWF1GxqD01as3sLG1G3kqImPtKT3BIkQrNqZ5q9BhLJkid1999QaAyfQz32NxPc91U+RuKyaR\nu6kwCHEL2zGVYgGv3dg0C3fieWgAXlpPboXwsilqF5crgUXuzl9uA4jXt8wCd/zZcc2WTx0tgmiy\nIndWbCzi4kOG76dnLndiE7Zj+J46f7kd2YZPbiyxyF27F8vnTYVBGChgxrfEND6vgK9dvRG5qJ0T\nljaYFHFmVQGDDUWev2LOHGM0/Cxwx58dVz/P5XM4USlO1PA3W9GK2jnh++krV66jUopH2I7h1cjz\nV25EKmrnZCDsF89KcCoMAstHxLnEBPYOTHENjoCRv7yy1sf13mRE7qJWOXXDPkuN07cMDGaPhyIW\ntXNSn7DInREbi07UzslCuYBDc8aqIPY+ntSzHHPq6VQYhLiF7Rj7552JaVkN2ALLE6pYbra6qJYK\nsdYD2P3YcQnbMexfXopY1M7Jkhlk3Z1QzUkzwp3h3CAi6/PifpYP2+6puFyhwEDkLlErBCK6m4gu\nENFFInrI5e9ERA+bf3+OiO4Ydy4R/TgRvUBEu0R0Ts/luDOJQhZg4KLK5yhSUTsnTn2fuIlq8/FR\n2FcIcQnbMbxCiHNw5M/b2NrFq9fjrzkZbPgUcz+bnxd3xmDOtgqKu595C9E4GPvkEFEOwEcB3APg\ndgDvIKLbHYfdA+Cs+e8BAI94OPd5AP8QwP8OfxmjiVvYjmEXVZwzZWAQZJ2UOyEO3SYncQbtnRyY\nzZltiHdwHKjbxt/Pl01Ru7i/dx6MC7OTc27EbQTjdA16+VbvBHBRKdVUSvUBPA7gPscx9wH4hDJ4\nCsA8Ed066lyl1NeUUhe0XckI4ha2Y3hFEre/kwtaJhFYXu31ca3bjy39kon7IbXDhVKnY3QLAu57\nSsdF3IkDDK8EOxOKjxltiN8Itrv9fXu0R4EXP8YxAC/bfn8FwJs9HHPM47mRE7ewHTNrLjNPVOJJ\nUbOzVCvh8xdaeOuHP2+8oAAFo7qUPc5KAQrK+N/mhuZj7H8338L82fna4Hj2Z8f90MS9CrPDcYPX\nHZ6L9XOPlgo4PDeL3/jcN/E7T10GhvSJ8drefubNdZz9bL83YHvNefzm9g4A4EzMhvh1R4zvOL5I\nzX7iTk6xMo1W1vCmUjXSz4rPsR0QInoAhhsKJ0+eDPQeZxfL+OE33KqzWZ5406kKfubvL+Gn33Im\n9s9+1985jdkZcwFIxgNEROb/1svWa8Yx5Pjb4DXig6zXHX83P5eIUDqQw1vOLsRynXb+449/V+yD\nMgD80j/4Ttz+hZfw3ScrsX4uEeHn3v638MVLbfOF/f1s7xdnPw/+tr+fh94HGBjA+mI5clE7J991\nfB7vf+vr8Y+/50SsnwsAn/znb8arq/HHa77tlkP4oe+4BYVc9BNaGrcNHxF9L4APKaV+yPz9AwCg\nlPr3tmN+C8DnlVK/Z/5+AcD3Azjt4dzPA/jXSqnz4xp77tw5df782MMEQRAEG0T0jFJqbPKOlxjC\n0wDOEtEZIioAuB/AE45jngDwTjPb6C4A15VSVz2eKwiCICSAses9pdQ2Eb0PwKcB5AA8ppR6gYge\nNP/+KIAnAdwL4CKAHoB3jzoXAIjoRwH8ZwA1AH9KRM/ySkIQBEGIn7EuoyQhLiNBEAT/6HQZCYIg\nCFOAGARBEAQBgBgEQRAEwUQMgiAIggBADIIgCIJgkqosIyJqAbgc8PQFACsam6MLaZc/pF3+kHb5\nI6ntAsK17ZRSqjbuoFQZhDAQ0XkvaVdxI+3yh7TLH9IufyS1XUA8bROXkSAIggBADIIgCIJgMk0G\n4WOTbsAQpF3+kHb5Q9rlj6S2C4ihbVMTQxAEQRBGM00rBEEQBGEEU2EQiOhuIrpARBeJ6KEYPu9F\nIvoKET1LROfN16pE9Fki+qb5f8V2/AfMtl0goh+yvf4m830uEtHDxDuTeG/HY0S0TETP217T1g4i\nOkBEv2++/gUiOh2iXR8ioivmd/YsEd07gXadIKK/JKKvEtELRPSzSfjORrRrot8ZEc0R0ReJ6Mtm\nu34xId/XsHZN/B4zz80R0d8Q0aeS8H3tQSmV6X8wZLcbAJYAFAB8GcDtEX/miwAWHK/9KoCHzJ8f\nAvAfzJ9vN9t0AMAZs605829fBHAXjI2q/gzAPT7b8X0A7gDwfBTtAPAeAI+aP98P4PdDtOtDMDZK\nch4bZ7tuBXCH+fMhAN8wP3+i39mIdk30OzPfo2z+nAfwBfO9J/19DWvXxO8x8/h/BeB3AXwqKc+k\n1TY/B6fxH4DvBfBp2+8fAPCBiD/zRew3CBcA3Gr+fCuAC27tgbF3xPeax3zd9vo7APxWgLacxt6B\nV1s7+Bjz51kYRTMUsF3DHtZY2+X47P8B4G1J+c5c2pWY7wxAEcCXYOyZnpjvy9GuiX9fAI4D+ByA\nt2JgEBLzfU2Dy+gYgJdtv79ivhYlCsCfE9EzZOwJDQC3KGMXOQB4DcAtY9p3zPzZ+XpYdLbDOkcp\ntQ3gOoCjIdr2fiJ6jgyXEi+bJ9Iuc6n93TBml4n5zhztAib8nZnuj2cBLAP4rFIqEd/XkHYBk7/H\n/hOAnwewa3tt4t8XMw0GYRK8RSn1RgD3AHgvEX2f/Y/KMN8TT+9KSjtMHoHh1nsjgKsAPjyphhBR\nGcAfAfiXSqkb9r9N8jtzadfEvzOl1I55rx8HcCcRfafj7xP5voa0a6LfFxH9MIBlpdQzw46Z9DM5\nDQbhCoATtt+Pm69FhlLqivn/MoA/AXAngG8R0a0AYP6/PKZ9V8yfdbdbZzusc4hoFsARANeCNEop\n9S3zId4F8HEY31ns7SKiPIxB95NKqT82X574d+bWrqR8Z2ZbVgH8JYC7kYDvy61dCfi+/i6AHyGi\nFwE8DuCtRPTfkKDvaxoMwtMAzhLRGSIqwAi0PBHVhxFRiYgO8c8A3g7gefMz32Ue9i4YfmCYr99v\nZgecAXAWwBfNJeQNIrrLzCB4p+2cMOhsh/29/hGAvzBnOL7hB8LkR2F8Z7G2y3yf/wLga0qpX7f9\naaLf2bB2Tfo7I6IaEc2bPx+EEdf4egK+L9d2Tfr7Ukp9QCl1XCl1GsY49BdKqZ+a9PflbGTm/wG4\nF0ZmRgPAByP+rCUYmQFfBvACfx4MP97nAHwTwJ8DqNrO+aDZtguwZRIBOAfjpm0A+E34Dz7+Hoyl\n8RYMP+NP62wHgDkAfwjgIoysh6UQ7fodAF8B8Jx5U986gXa9BcZy/TkAz5r/7p30dzaiXRP9zgC8\nAcDfmJ//PIBf0H2va27XxO8x2/t+PwZB5Yk/k/xPKpUFQRAEANPhMhIEQRA8IAZBEARBACAGQRAE\nQTARgyAIgiAAEIMgCIIgmIhBEARBEACIQRAEQRBMxCAIgiAIAID/D6di+i+d9ToxAAAAAElFTkSu\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcefa3fa3c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr = lambda x: 1/(5**(x*0.0001))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(scale_fn=clr, scale_mode='iterations')\n",
    "\n",
    "model.compile(optimizer=RMSprop(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef38d9438>"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef28554e0>]"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+0f20O6+Sp/ec5EuXJDIjNtTucHr0rU9PoaGljb++n2t3KMpmmiguQE19M4eK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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef38d9f60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Adagrad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='triangular')\n",
    "\n",
    "model.compile(optimizer=Adagrad(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef232e208>"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular],verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef23d05f8>]"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SMD66OY6ZNJLZmVFakO1J2Z2ijnheZhcPB0ICudgbldl5dTWl7eCTDdmddyYv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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef38d9710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='triangular2')\n",
    "\n",
    "model.compile(optimizer=Adagrad(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef2d69ba8>"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=20, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular._reset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef2d696a0>"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcefa3094a8>]"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2SwuEaINS8S3szFYePjHOqs52BleuqPhYv6+Ni3o61bGslM18lnJj5kq/nYun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\n5FGBoCiKogDwfwAC8F0kV6KlTAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef2d69630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='exp_range', gamma=0.99994)\n",
    "\n",
    "model.compile(optimizer=Adagrad(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcefa317208>"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=20, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef309e470>]"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Ikn4Fx2ZuRJvdpHpBuDKWfIVyPJ01pZj1rMLpWVV6WTnj3V4nDjXY8EhHJYJhge4Jd66X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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcefa317860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular._reset(new_base_lr=0.003, new_max_lr=0.009)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef2be8a58>"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fceffece908>]"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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HnJocrI5+WbRqNrrYO4Xf5+HAJmVwnMaKINQAvTHP+4xjVsZsOFdEngf6lVKX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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef25085f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr = lambda x: 0.5*(1+np.sin(x*np.pi/2.))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(scale_fn=clr, scale_mode='cycle')\n",
    "\n",
    "model.compile(optimizer=Adagrad(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef21e9908>"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=40, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef233a8d0>]"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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dsw59Hy4y1RNDCC9wx6J2bpM7FrlL4krQU423UupJGIO+/bVHbT8rAO/1eq75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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef9db3588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr = lambda x: 1/(5**(x*0.0001))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(scale_fn=clr, scale_mode='iterations')\n",
    "\n",
    "model.compile(optimizer=Adagrad(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fceffc00320>"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef31b3518>]"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+0f20O6+Sp/ec5EuXJDIjNtTucHr0rU9PoaGljb++n2t3KMpmmiguQE19M4eK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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef31b72b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Adadelta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='triangular')\n",
    "\n",
    "model.compile(optimizer=Adadelta(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef347c3c8>"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular],verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcefa63a0f0>]"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SMD66OY6ZNJLZmVFakO1J2Z2ijnheZhcPB0ICudgbldl5dTWl7eCTDdmddyYv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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef43c32e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='triangular2')\n",
    "\n",
    "model.compile(optimizer=Adadelta(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef43e26d8>"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=20, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular._reset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef273f160>"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef3f21358>]"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2SwuEaINS8S3szFYePjHOqs52BleuqPhYv6+Ni3o61bGslM18lnJj5kq/nYun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\n5FGBoCiKogDwfwAC8F0kV6KlTAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcefa784278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='exp_range', gamma=0.99994)\n",
    "\n",
    "model.compile(optimizer=Adadelta(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef2261a20>"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=20, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcefa249fd0>]"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Ikn4Fx2ZuRJvdpHpBuDKWfIVyPJ01pZj1rMLpWVV6WTnj3V4nDjXY8EhHJYJhge4Jd66X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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef22610b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular._reset(new_base_lr=0.003, new_max_lr=0.009)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef2c56748>"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef34d3e80>]"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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HnJocrI5+WbRqNrrYO4Xf5+HAJmVwnMaKINQAvTHP+4xjVsZsOFdEngf6lVKX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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef3b695f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr = lambda x: 0.5*(1+np.sin(x*np.pi/2.))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(scale_fn=clr, scale_mode='cycle')\n",
    "\n",
    "model.compile(optimizer=Adadelta(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcefa1eff98>"
      ]
     },
     "execution_count": 175,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=40, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef30ff860>]"
      ]
     },
     "execution_count": 176,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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dsw59Hy4y1RNDCC9wx6J2bpM7FrlL4krQU423UupJGIO+/bVHbT8rAO/1eq75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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcefa678d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr = lambda x: 1/(5**(x*0.0001))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(scale_fn=clr, scale_mode='iterations')\n",
    "\n",
    "model.compile(optimizer=Adadelta(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef2d828d0>"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef2334748>]"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+0f20O6+Sp/ec5EuXJDIjNtTucHr0rU9PoaGljb++n2t3KMpmmiguQE19M4eK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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef31cbeb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Adam"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='triangular')\n",
    "\n",
    "model.compile(optimizer=Adam(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef9d0eba8>"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular],verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef0f8f7f0>]"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SMD66OY6ZNJLZmVFakO1J2Z2ijnheZhcPB0ICudgbldl5dTWl7eCTDdmddyYv\nKWsyu/SbdLgRPllCX3AWt0a9I7vzq0E83lSOsgLvyuzi4UBIIIbM7vE0ktmZ0VFbjIZy78jujEmH\nR1urkJ+THu3KVvB5THZ3X2bn/closXAgJIjVcATnuzWcTDOZnRmxsru5JffL7tR702kpszPDkN15\nJRDO6vNnfGnmqLJ05SKiZ4ioh4j6iejldd4nIvq+/v5nRLTf7Fgi+n193+tEdJaIdiWmSvbw8Z1J\nTMyvpN0dhRV8soTl1Qgu9bl/8pIhszvZkV4XCiucliVcve0N2Z2iamiXirG7ssDuoqQU00AgokwA\nPwDwLAAZwPNEJMft9iyAVv3nRQCvWDj2D4UQ3xBCPALgpwB+d+fVsQ9FHUFOZgaOtXO7cjyPN1Wg\nND/bE3eP/oCG/bvL01JmZ4ZPrkVERN0/bmZibhlXbo2n5VOglSeEgwD6hRCDQohlAD8BcCZunzMA\nfiyiXAZQRkR1mx0rhJiOOb4QgGtntRjtyof1WZvMV8nOzMCJ9mqc79awGo7YXZxt8+WkIbNLvwuF\nFR6sL0FtSZ7rdSXnu4OIpOlcIiuBUA9gKOb1XX2blX02PZaI/hURDQH4Zbj4CaE/OItbY/Np+QWy\nik+uxcT8iqtld/40WSRluxARuuQaXOwddbXszh/QIJXk4qE0kNnFY2vvpxDie0KIRgB/BuA76+1D\nRC8S0VUiuhoKhVJbQIsYMrt064DaCsfaq5GTmeHqZiNF1dBSVYi91UV2F8Wx+ORaLKyE8V6/O/uL\n1mR2nekhs4vHSiAMA2iMed2gb7Oyj5VjgWgg/N31PlwI8ZoQ4oAQ4kB1tTPb5xVVwzcaSlFbmmd3\nURxLUW4WjuythBJwp+wuVmbHbMzhlgpXy+4+GIjK7NLVVGwlEK4AaCWiZiLKAfAcgDfi9nkDwAv6\naKPDAKaEEPc2O5aIWmOOPwOge4d1sYU1mR0/HZjikyXcdqns7h2W2VkiNysTx9rdK7s7q2oozMnE\nE3vTQ2YXj2kgCCFWEW3OeQtAAMDrQogbRPQSEb2k7/YmgEEA/QB+COBbmx2rH/NviOgLIvoMwGkA\nv5W4aqUOYwau7wG+UJjRpYemGxdmN2R2j7LMzpTTsoTR2SVcd5nsLhIR8Ac0HGuvRm5Wek46tDQk\nRgjxJqIX/dhtr8b8LgB82+qx+vZ1m4jchiGza5dYZmdGrOzu2yf22V0cyyyvRvBOTxDPPljLMjsL\nHG+7L7uXQ6rgAAAVr0lEQVRzkw3207uTCKWZzC4enlK7A+aWojK7dF8kZSv4DNndtHtkd/dldjzp\n0AqlBdk41Ow+2Z0/oCEzg3CiPX1kdvFwIOyAS30hLK9G0vqOYqsYTWt+F8nuFHUEedkZeGpfld1F\ncQ0+WUJ/MLq2uFtQVA0HmyrSSmYXDwfCDjiraijNj6p/GWu0S8VorMh3zeQlY9LhU/uqWWa3Be7L\n7txxnm+PzaFXm03b0UUGHAjbZDUcwdvd0UVSslhmZxkigq+zFu8NjLlCdnfjy2l8ObXISvMt0lBe\ngM66EvhVdzwJGs1b6X6e+Uq2Ta7dntBldun9BdoO92V3zpxoGMuazK4zfduVt4vPRbK7s6qGjtpi\nNFakl8wuHg6EbaKoGnIyM/B0mzMnyzmZx5vKUZqf7Yrhp/6Ahsd2l6OqiGV2W8XXKSEigHMOX1N7\nfG4ZV9NUZhcPB8I2EEJACWg4wjK7bZGVmYGTHTU43x10tOxueHIBN75kmd12ebC+BHWleY4fbfR2\nGsvs4uFA2AZ9wVncZpndjvDJEibnV3DVwbI7v34hS/eOxu1CROjqlHCpz9myO0VNX5ldPBwI28C4\n4+FA2D5Pt0Vld34H3z0qqoaWapbZ7QSfLDladre4EsbFvqjMjucScSBsC0XV8HBDKaQSltltl6Lc\nLDyxz7myu6kFltklgsMtlSh2sOzu/YFRzC+H+TzrcCBskeC0LrPjL9COMWR3fQ6U3b3TE8RqRKT9\nMMSdkpOV4WjZnaJqayZehgNhyxgzbLldeecYsjsn3j36A0FUFeXgkUb3uHicik+X3X0y5CzZXVRm\nF8SxtvSV2cXDgbBFFHUEjRUss0sEUkkeHm4oddzw0+XVCN7pDuJUh8QyuwRwvL0GWbrszkmwzO7r\ncCBsgbmlVbw3MAZfZy13QCUInyzh06FJaA6S3X14cwwzS6v8FJggSvOzcailwnEaC0VlmV08HAhb\n4GIvy+wSjWEQPecg2Z2iaiyzSzC+TgkDoTkMhpzTX2TI7EoLsu0uimPgQNgCSkBDWUE2Hm/iduVE\n0SYVYXdFgWPuHoUQ8KsajrayzC6RGE9bfofMWr41Ooe+4Czf3MXBgWCR1XAE57uDONnOMrtEQkTw\nyZJjZHeGzI4vFImlobwAcl2JY/oReC7R+vCVzSJXb09gkmV2SaGrMyq7u9hrv+xOUTVkEHCqg9uV\nE02XLOHa7QmMzS7ZXRQoLLNbFw4Eixgyu6Mss0s4jzeVo6wg2xF3j4qq4bE95ahkmV3COS3rsrtu\ne/uLxueWcfX2OM8xWQcOBAsYi6Q8sY9ldskgKzMDJ9trcL7HXtnd3Yl5qPem1+ZHMInlgV0l2OUA\n2d35NZkdL4kaDweCBXq1WdwZZ5ldMnGC7M7P7cpJhYjQJUu41BeyVXanqCOoLcnDg/UltpXBqXAg\nWMAYGcF3jsnj6bZq5GRl2Hr3qAQ07K0uRAvL7JKGT5awuBLBu332yO4WV8K42DuKLrmG5xKtAweC\nBc6qGh5uLGOZXRIpzM3Ck3sroaj2yO6mFlbw4eA4NyMkmUPN9sru3usfxcJKmM/zBnAgmKBNL+LT\noUnugEoBXbKEO+Pz6NVSP3nJkNlxc1FyMWR357o1hG2Q3Rkyu8MtFSn/bDfAgWACNxeljvuyu9RP\nUlNUDVVFOXi0sSzln51uRGV3y7g+lNr+ojWZXTvL7DaCA8EERdWwu6IAbRK3KycbqSQPDzeWpbw5\nYXk1ggs9IZzqkJDBMrukY8juUi01vH53EqOzS/y0vwkcCJswu7SK9/uji6RwB1RqOC1L+PTuVEpl\nd5cHozI7bi5KDaX52TjcUpny1fIMmd3xNp50uBEcCJtwqTeE5TDL7FKJzwbnjaJqyM/OxFOtLLNL\nFT459bI7RdVwqJlldpvBgbAJihqV2R3YwzK7VNFaY8juUhMIQgj4AxqOtlYhL5vblVPFqc7oXXqq\nzvPN0Tn0s8zOFA6EDVgNR3C+J4iTHSyzSyWG7O79/jHMpkB2d+PLadxjmV3KSbXszhiowOd5c/hK\ntwFXbukyOx5dlHJ8soTlcGpkd2d1md1JltmlHJ8s4dqdCYymQHbnV4PorCtBQznL7DbDUiAQ0TNE\n1ENE/UT08jrvExF9X3//MyLab3YsEf0hEXXr+/9vInLUeD9F1ZCTlYGnWWaXcg7sSZ3sjmV29uGT\nJQgBnE/y4kiGzI6fDswxDQQiygTwAwDPApABPE9EctxuzwJo1X9eBPCKhWMVAA8KIb4BoBfAd3dc\nmwQhhIASGMGTeytRyDK7lJOVmYGTHTU4351c2d3Q+DwC96b5QmETD+wqQX1ZPpQkDyA4F9CiMjt+\n2jfFyhPCQQD9QohBIcQygJ8AOBO3zxkAPxZRLgMoI6K6zY4VQpwVQhiNxJcBNCSgPgmhV5vF0PgC\nT2+3kdOyhKmFFVy5lbzJS8ZIJj7P9kBE6OqswaW+EBaWkye7U1QNdaUss7OClUCoBzAU8/quvs3K\nPlaOBYB/COBv1/twInqRiK4S0dVQKDULqBgdUF2d3K5sF0dbky+7U1QN+2qK0FxVmLTPYDany5Dd\n9SdHdre4EsalvlF0dfJcIivY3qlMRN8DsArgz9Z7XwjxmhDigBDiQHV1atrzFVXDI41lqGGZnW2s\nye4CI0mR3U3Nr+DDm9yubDf3ZXfJ0ZW822fI7Pg8W8FKIAwDaIx53aBvs7LPpscS0a8B+FkAvyzs\nUFyugza9iE/vTvEXyAH45FoMjS+gR5tJ+N9+pzeIMMvsbCcnKwPHO2pwLhBMiuzOH9BQnJuFwy2V\nCf/bXsRKIFwB0EpEzUSUA+A5AG/E7fMGgBf00UaHAUwJIe5tdiwRPQPgdwD8nBBiPkH12TG8+LZz\nMJrslBuJbzY6q2qoKsrFIw2OGtyWlvhkCWNzy/jkTmL7i2JldjlZtjeGuALTfyW94/c7AN4CEADw\nuhDiBhG9REQv6bu9CWAQQD+AHwL41mbH6sf8MYBiAAoRXSeiVxNXre2jqBr2VBagtYZldnZTU5KH\nRxrLEq6xWFoN40JPCF2dNSyzcwDH26uRnUkJH230yVBUZsc3d9axNKZSCPEmohf92G2vxvwuAHzb\n6rH69n1bKmkKmF1axQcDY3jhyB7ugHIIPlnCH77VA216MWELFF0eHMcsy+wcQ0leVHanqBq++2xn\nwv6uomrIyiAcb+fBIVbh56gYLrLMznEY5yKRo40UdQT52Zl4ch/L7JxCV6eEwdAcBhIou1PUERxq\nqUBpPsvsrMKBEIOiaigvyMZjLLNzDK01RdhTmTjZnRACfjWIp9tYZuckuhIc/IOhWQyE5ngy2hbh\nQNBZCUdwvjuIEyyzcxREBF+nhA8GEiO7+2J4GiPTizwZzWHUl+XjgV2Jk92trXTIT/tbgq98Oldu\njWNqYYVXU3IghuzuQs/OJyYq6gjL7ByKT5bw8Z0JhGZ2LrtTVA0yy+y2DAeCjiGzO9rKMjun8die\ncpQXZCdktNFZVcOBPRWoKMxJQMmYRGLI7t7u3pnsbmx2CdduT/DTwTbgQMD9RVKe2lfFMjsHEpXd\nSTjfHcTKDmR3Q+Pz6B6Z4UEDDkWui8rudrrW8rnuICIC/LS/DTgQAPRoM7rMjr9ATsUn1+iyu/Ft\n/w2edOhsDNndu/07k90pqoZdpXl4YBfL7LYKBwLuz4Q9xTI7x5II2Z0/oKG1pghNLLNzLD65Fosr\nEVzq215/0cJyGJf6QuiSWWa3HTgQACgBXWZXzDI7p1KYm4Wn9lVBUbVtye5YZucODrVUoDgva9vB\n/17/KBZXeC7Rdkn7QBiZWsRnLLNzBT5Zwt2JBXSPbF1293YPy+zcQHZmBk60RxdH2o7sTlGjMrtD\nzSyz2w5pHwiGP4U7oJzPqc4aEAH+bdw9KqqG6uJcPMwyO8ezXdldOCJwrltjmd0OSPt/NUXV0FRZ\ngH0ss3M8NcVR2d1WJWhLq2G80xNkmZ1LOGbI7rYY/NeHJjA6u8xPgTsgrQNhZnEFHwyMwscdUK6h\nq1PCZ3enMDK1aPmYDwbGMLfMi6S4hVjZ3VY4yzK7HZPWgXCxdxQrYcEaAxdhNO1t5SnBH9BQkJOJ\nJ/ayzM4t+GQJg6Nz6A9al90pqobDLZUss9sBaR0IijqC8oJs7N/N7cpuYV9NEZq2ILtbk9m1VrPM\nzkV0dW5NdjcQmsVgaI6fAndI2gaCIbM72SGxzM5FEBF8soQPBkYxs7hiuv/nw1O6zI4vFG5iV1k+\nHqwvsbzWsjHQgHUVOyNtr4RXbo5jepEXSXEjPrkWK2GBi72jpvsqqoYMAk6wzM51+Dpr8cnQpCXZ\nnSGzqy/LT0HJvEvaBsJZVUNuVgaebuN2ZbdhyO6s3D0qqoYDTSyzcyOG7O589+bNRqOzS7h2Z4Jv\n7hJAWgZCrMyuIIdldm4jM4Msye4MmR3PMXEnnXXFqC/LN+1HOB8IQgh2VCWCtAyE7pEZ3J1gmZ2b\n8ckSphdXceXmxrK7syyzczVGf9GlvlHML2+8ONJZVVtbYIfZGWkZCIqqgQg4yTI71/J0WxVyszI2\nVSX7VQ1tUhH2VLLMzq34ZAlLqxFc6lu/v2hhOYx3+0Po6qzhuUQJIG0DgWV27qYgZ3PZ3eT8Mj66\nxTI7t3OwuQIlm8ju3l2T2fFcokSQdoFwb2oBnw+zzM4L+GQJw5Pry+4MmV0XL7LuarIzM3CiY2PZ\nnaKOoDg3CwebK2wonfdIu0AwxitzR6P7OdUpgWj9yUuKqqGGZXaewCdLGJ9bxsdxsrtwROBcIIjj\nHTUss0sQafevqASCaK4qxN5qltm5neri3KjsLi4QllbDuNATwqlOiWV2HuBY2/qyu0/uTGBsjmV2\niSStAoFldt7DJ0v4fHgK96YW1ra9r8vs+CnQGxTHyO5i+4sUVUN2JuF4e7WNpfMWaRUIF3pDWAlz\nu7KXMC76sWsk+NWozO7IXl4kxSucliXcHJ3DQOi+7E4JRGV2JXkss0sUaRUIiqqhojAHj+0pt7so\nTILYW12E5qrCteGnkUh00uGxNpbZeQnDUWScZ5bZJYe0CYSVcARvdwdxsqMGmdyu7BmMyUuXB8cw\ns7iCz4enoE0v8VOgx6grzcdD9aVrT4JGf8IpPs8JJW0C4SOW2XkWnyxhJSxwoTcERdV0tQVPOvQa\nPllak90pqoYHdrHMLtFYCgQieoaIeoion4heXud9IqLv6+9/RkT7zY4lol8kohtEFCGiA4mpzsYo\nuszuaCvL7LzG/t3lqCjMgaJqUZndnnKUs8zOc3R1RmV3r18dwscss0sKpoFARJkAfgDgWQAygOeJ\nSI7b7VkArfrPiwBesXDsFwB+AcDFnVdjc4QQUFQNR1tZZudFjCeCv7n+JXq0Gb5QeBRDdveHb/Ww\nzC5JWHlCOAigXwgxKIRYBvATAGfi9jkD4MciymUAZURUt9mxQoiAEKInYTXZhMC9GQxPLnC7soeJ\nvTicZo2BJzH6iwCgojAHch3L7BKNlUCoBzAU8/quvs3KPlaOTTqGzI47oLxLbFPg7soCG0vCJBMj\nEPZVF/FcoiTg+PYTInoR0WYo7N69e1t/o7Y0F7/4WAOqi3MTWTTGQRTkZOFf/8JDqC1hYaGXOdRc\ngZeO7cXzBxvtLoonsRIIwwBi//Ub9G1W9sm2cOymCCFeA/AaABw4cODrdisL/NLju/FLj28vTBj3\n8PxBPsdeJyszAy8/22F3MTyLlSajKwBaiaiZiHIAPAfgjbh93gDwgj7a6DCAKSHEPYvHMgzDMA7A\n9AlBCLFKRN8B8BaATAA/EkLcIKKX9PdfBfAmgG8C6AcwD+AfbHYsABDRzwP4TwCqAfxfIrouhPiZ\nRFeQYRiGsQatt7iIUzlw4IC4evWq3cVgGIZxFUR0TQhhOt8rbWYqMwzDMJvDgcAwDMMA4EBgGIZh\ndDgQGIZhGAAcCAzDMIyOq0YZEVEIwO1tHl4FYDSBxXEDXOf0gOucHuykznuEEKZrjboqEHYCEV21\nMuzKS3Cd0wOuc3qQijpzkxHDMAwDgAOBYRiG0UmnQHjN7gLYANc5PeA6pwdJr3Pa9CEwDMMwm5NO\nTwgMwzDMJqRFIBDRM0TUQ0T9RPSy3eXZLkTUSERvE5FKRDeI6Lf07RVEpBBRn/7f8phjvqvXu4eI\nfiZm+2NE9Ln+3vfJ4ctPEVEmEX1CRD/VX3u6zkRURkR/SUTdRBQgoiNpUOff1r/XXxDRnxNRntfq\nTEQ/IqIgEX0Rsy1hdSSiXCL6C337h0TUtKUCCiE8/YOodnsAQAuAHACfApDtLtc261IHYL/+ezGA\nXgAygD8A8LK+/WUA/1b/XdbrmwugWf93yNTf+wjAYQAE4G8BPGt3/Uzq/k8A/A8AP9Vfe7rOAP4b\ngF/Xf88BUOblOiO6tO5NAPn669cB/JrX6gzgaQD7AXwRsy1hdQTwLQCv6r8/B+AvtlQ+u/+BUnAC\njgB4K+b1dwF81+5yJahufwPAB6AHQJ2+rQ5Az3p1RXRdiiP6Pt0x258H8J/trs8m9WwAcA7AyZhA\n8GydAZTqF0eK2+7lOhvrr1cguk7LTwGc9mKdATTFBULC6mjso/+ehehENrJatnRoMjK+aAZ39W2u\nRn8UfBTAhwAkEV2hDgBGAEj67xvVvV7/PX67U/mPAH4HQCRmm5fr3AwgBOC/6s1kf0JEhfBwnYUQ\nwwD+HYA7AO4huuriWXi4zjEkso5rxwghVgFMAai0WpB0CATPQURFAP4XgH8shJiOfU9Ebw08M3SM\niH4WQFAIcW2jfbxWZ0Tv7PYDeEUI8SiAOUSbEtbwWp31dvMziIbhLgCFRPQrsft4rc7rYXcd0yEQ\nhgE0xrxu0Le5EiLKRjQM/kwI8Vf6Zo2I6vT36wAE9e0b1X1Y/z1+uxN5EsDPEdEtAD8BcJKI/hTe\nrvNdAHeFEB/qr/8S0YDwcp27ANwUQoSEECsA/grAE/B2nQ0SWce1Y4goC9HmxzGrBUmHQLgCoJWI\nmokoB9GOljdsLtO20EcS/BcAASHEf4h56w0Av6r//quI9i0Y25/TRx40A2gF8JH+eDpNRIf1v/lC\nzDGOQgjxXSFEgxCiCdFzd14I8Svwdp1HAAwRUbu+6RQAFR6uM6JNRYeJqEAv6ykAAXi7zgaJrGPs\n3/p7iP7/Yv2Jw+4OlhR14nwT0RE5AwC+Z3d5dlCPpxB9nPwMwHX955uIthGeA9AHwA+gIuaY7+n1\n7kHMaAsABwB8ob/3x9hCx5ON9T+O+53Knq4zgEcAXNXP9V8DKE+DOv8LAN16ef87oqNrPFVnAH+O\naB/JCqJPgv8okXUEkAfgfwLoR3QkUstWysczlRmGYRgA6dFkxDAMw1iAA4FhGIYBwIHAMAzD6HAg\nMAzDMAA4EBiGYRgdDgSGYRgGAAcCwzAMo8OBwDAMwwAA/j9h9H7xyCU/ewAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcefa678710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='triangular2')\n",
    "\n",
    "model.compile(optimizer=Adam(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fceefde1f98>"
      ]
     },
     "execution_count": 186,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=20, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular._reset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fceefe39b00>"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fceef9ac160>]"
      ]
     },
     "execution_count": 189,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2SwuEaINS8S3szFYePjHOqs52BleuqPhYv6+Ni3o61bGslM18lnJj5kq/nYun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\n5FGBoCiKogDwfwAC8F0kV6KlTAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fceefb8a4e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='exp_range', gamma=0.99994)\n",
    "\n",
    "model.compile(optimizer=Adam(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef23242b0>"
      ]
     },
     "execution_count": 191,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=20, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef27463c8>]"
      ]
     },
     "execution_count": 192,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Ikn4Fx2ZuRJvdpHpBuDKWfIVyPJ01pZj1rMLpWVV6WTnj3V4nDjXY8EhHJYJhge4Jd66X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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef2324cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular._reset(new_base_lr=0.003, new_max_lr=0.009)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef0f31080>"
      ]
     },
     "execution_count": 194,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef2a41668>]"
      ]
     },
     "execution_count": 195,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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HnJocrI5+WbRqNrrYO4Xf5+HAJmVwnMaKINQAvTHP+4xjVsZsOFdEngf6lVKX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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef2324c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr = lambda x: 0.5*(1+np.sin(x*np.pi/2.))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(scale_fn=clr, scale_mode='cycle')\n",
    "\n",
    "model.compile(optimizer=Adam(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef0d0eb00>"
      ]
     },
     "execution_count": 198,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=40, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef226c7f0>]"
      ]
     },
     "execution_count": 199,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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dsw59Hy4y1RNDCC9wx6J2bpM7FrlL4krQU423UupJGIO+/bVHbT8rAO/1eq75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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef0ba4198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr = lambda x: 1/(5**(x*0.0001))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(scale_fn=clr, scale_mode='iterations')\n",
    "\n",
    "model.compile(optimizer=Adam(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcefa322160>"
      ]
     },
     "execution_count": 202,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcefa26b390>]"
      ]
     },
     "execution_count": 203,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+0f20O6+Sp/ec5EuXJDIjNtTucHr0rU9PoaGljb++n2t3KMpmmiguQE19M4eK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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcefa3225c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Adamax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='triangular')\n",
    "\n",
    "model.compile(optimizer=Adamax(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7f8f3bb75cc0>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular],verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f8f3c0aeac8>]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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LlE5VQ0GKw+zMBGUJV+9NYIDD7jJGUTU8sbMS1Q4Ks0vEBcHBFFVDRXEeOjLQr2x4bHsF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\nMcYAcEFgjDGm44LAGGMMAPD/ARmAgG/Du//XAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f8f3bb75f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='triangular2')\n",
    "\n",
    "model.compile(optimizer=Adamax(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef2360438>"
      ]
     },
     "execution_count": 209,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=20, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular._reset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef31c6dd8>"
      ]
     },
     "execution_count": 211,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef3041160>]"
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2SwuEaINS8S3szFYePjHOqs52BleuqPhYv6+Ni3o61bGslM18lnJj5kq/nYun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\n5FGBoCiKogDwfwAC8F0kV6KlTAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef34a29e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='exp_range', gamma=0.99994)\n",
    "\n",
    "model.compile(optimizer=Adamax(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef0aed898>"
      ]
     },
     "execution_count": 214,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=20, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef3477a90>]"
      ]
     },
     "execution_count": 215,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Ikn4Fx2ZuRJvdpHpBuDKWfIVyPJ01pZj1rMLpWVV6WTnj3V4nDjXY8EhHJYJhge4Jd66X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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef0aedef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular._reset(new_base_lr=0.003, new_max_lr=0.009)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef2be6518>"
      ]
     },
     "execution_count": 217,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcf00acce10>]"
      ]
     },
     "execution_count": 218,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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HnJocrI5+WbRqNrrYO4Xf5+HAJmVwnMaKINQAvTHP+4xjVsZsOFdEngf6lVKX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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef2bde320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr = lambda x: 0.5*(1+np.sin(x*np.pi/2.))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(scale_fn=clr, scale_mode='cycle')\n",
    "\n",
    "model.compile(optimizer=Adamax(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcefa658a58>"
      ]
     },
     "execution_count": 221,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=40, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef28e0e80>]"
      ]
     },
     "execution_count": 222,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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dsw59Hy4y1RNDCC9wx6J2bpM7FrlL4krQU423UupJGIO+/bVHbT8rAO/1eq75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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef0d0e048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr = lambda x: 1/(5**(x*0.0001))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(scale_fn=clr, scale_mode='iterations')\n",
    "\n",
    "model.compile(optimizer=Adamax(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef25df208>"
      ]
     },
     "execution_count": 225,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef222b400>]"
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+0f20O6+Sp/ec5EuXJDIjNtTucHr0rU9PoaGljb++n2t3KMpmmiguQE19M4eK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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef25df860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Nadam"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='triangular')\n",
    "\n",
    "model.compile(optimizer=Nadam(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fceefbab128>"
      ]
     },
     "execution_count": 228,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular],verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef9d800f0>]"
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SMD66OY6ZNJLZmVFakO1J2Z2ijnheZhcPB0ICudgbldl5dTWl7eCTDdmddyYv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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcefa3fa128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='triangular2')\n",
    "\n",
    "model.compile(optimizer=Nadam(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef0fbceb8>"
      ]
     },
     "execution_count": 232,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=20, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular._reset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcef10b9080>"
      ]
     },
     "execution_count": 234,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fceefb84198>]"
      ]
     },
     "execution_count": 235,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2SwuEaINS8S3szFYePjHOqs52BleuqPhYv6+Ni3o61bGslM18lnJj5kq/nYun\n8DiX9HVVlWu0flUHwRVtHBhpjbnS0gLButl6G+Yosy8D80C+wmm1SUKasaxUQiSepLujDV/b0iXW\n7cSuxZMxhgMjsarMRWCVjQ+2TBBGSwuE0XiCVZ3tRfsI2ElPVzsuqT0DczqV5rnIRNEOaaUYGgwS\nnUjO+VEUpRiROncVXIhdmf0nYwlOT6aqcihbWGXjE7MXfj/ylhYI0QbGVQN43C56umoPPX36ZJys\noWgP5VLM20ZbQxVWaiMykWyYuQhgdacXt0tqDj21cgiq1RAAtg90k84anj514ZeNb2mBkMtSbtxN\nDjlVuFaT0f4yeiiXYuuaIG6XqNlIKYtIAxM4IZcD0GdD3s7+cIw2t3D5mqXby5bC6r/cCkEYLS0Q\nRhusBkM+4aZGM81weJz+gK+mMsQr2t1sCfnZrxqCUoJM1jA2max7p7SF9AVqb6U5HB7n0n5/TWbh\n/oCPXr+3JeZKywqEdCbL6ckkoQbFVVuEAj6iE7Wteg6EK6twuhRDA0EOjLRem0ClMs5M5ZIpG65N\n+701CQRjDMPh6h3KFiLC0ECwJbTplhUIpydTGNO4kFOLUMDH2akUyXR1DqrYzCxHT0/VZC6yGFoX\nZHx6lhNnZ2r+LuXCJZLvGVLvxjgL6Q/Wlq384plpJhJphqrI1VnI0GA3z49NMpm8sPuRt6xAaHSi\njYUlgMaq1BIOWQlpNa56AIYGrIzlC18VVqqnUb2UFxIK+IjNzFYd3TNsg0PZYmgwiDFw8ALP7m9Z\ngdDo2iwWfTXGV1sOZTtWPZf2+2l3u1pCFVaqxwqCaLgPwW+Fnla3eBoOx/B6XGwOlW4vWwrLRHuh\nO5ZbViDMZSkHG2syqjUD88DIOOtWrWBlZ3vNY2n3uLh8jb9poadHxybJtlA3quVKJJ5EJJdH00is\nxVq1oacHwjGuWBugrcz2ssXo6fIy0L2iKY7lbNbw8KHRhhTYa1mBEIkncbuE1Z2N9yHkzl+lhnCi\ndidZIUOD3RwciTf8wXxwJMZrP/tTvvTIkYaeV6mcSCxBT5e37L7ddmEV0qtmrmSyhoMn7Z4ruSCM\nRvPTX4xxx9cf5+FDkbqfq2UFwmg8QW9XLvmlkazsaKPNLVVpCGcmk4yMz9jiULYYGgwymUxz9PSU\nbd9ZDvfsPQbA//+zYxrl5HAiE4mGm4tg3r9XjUB4fmyS6VSmpgzlhQwNdnPszDTj0ynbvrMc7tlz\njJ6udl7F0X3BAAAgAElEQVS3NVT3c7WsQIjEEw0POYVcCFufv7r46vkKp/ZqCNDYjOV4Ypb7nzxJ\nm1s4PZnk58+fadi5lcppRgInQGCFB6/HVdVc2X/CPoeyhSVcGqkljIzP8JNno7xj5zraPfV/XLes\nQIjGk4QaVNRuIblwuioEwokYIrny1XZxSV8XK9rcDXUsf++JEWZmM3zzvbsIrmhjd15bUJxJNJ5o\neMgp5BZP1YaeDodjdHk9XNRTfnvZUlj9mBs5V7659zgGeNd16xtyvpYVCJEGts5cSChQXcLNgZFx\nLurpxO8rvy9sKXJtAgMN0xCMMezec4wdg0F2blzF268Z5OFDEVv75yr2kUxnODOVanh4tkWoBm16\n20Cg4vayxQiuaGNTT+ec9lFvUuks9z52gtde2sfgyo6GnLMlBUJiNsP49GxT1GAgbzKqbNVjjGF/\nOFZVh7RSDA12c+hkY9oEPvrCWX4RneTWXRsAuHXXBtJZw72Pnaj7uZXKsfJl+hscjWfRF/BWnNmf\nSmd55mTcVnORRSMdyw8dGuX0ZJLb8nOlEbSkQLDimpulIfQHfUwm0xVlPUbiScYmkraUrFjI0GCQ\nZDrLLyKTtn/3Qr6+5xgBn4ffGFoLwKaeTl61uYdvPnrclnaJir1YC5dmmIwgN0dHY4mKAg+ei0yQ\nymRtdShbbB8IciqWIGpDT5NS7N5zjMGVK3j1lt66n8uiLIEgIteLyGEROSIiH1/kcxGRz+c/HxaR\nq0sdKyKfEZFn8/t/T0TsF+dL0OjWmQsJVVHrfb+NWZcLaZRjeWwiyUOHRnnbNetY0T5fbOzW6zZw\nKpbgJ89G63p+pXKaldFv0R/wMTObYaKCxdPcXLEx+MJix7rcd9Y7Qe0XkQn2vnCWd123vqGRkCUF\ngoi4gS8CNwBbgVtEZOuC3W4ANuf/7gDuLOPYHwLbjDFDwHPAJ2q+mjKxqo02TSD4K09OOxCO4XYJ\nW9fY51C22LCqA7/PMxfFVC/u23eC2Yzh1l0vdZD92uV99Ad87N57vK7nVyrHEgj9TYjIg+oa5RwI\nx+juaGPdqsrby5biirUBXDJfMaBe3LP3OG1u4R0719X1PAspR0O4FjhijDlqjEkB9wI3LtjnRuBu\nk2MP0C0ia4oda4x52Bhjif09wKAN11MW87VZmmUXrTy+en94nC0h/0tW1nbhcuXaBNZTQ8hkDd/Y\ne5xXXLyai3tfWkrA43Zx87Xr+Lfnxjh2prH5EEpxIvEkbW5hZYd9gQyVEKois39/uLb2ssXoaPew\nuc8/13inHkyn0nzn8TA3bFtDT1djn1HlCIQBoNDjF85vK2efco4F+G3gB4udXETuEJF9IrJvbGys\njOGWJjqRxOtxEVzRnJu80gxMqy+snQlpCxka7ObwaP3aBD5yOMrI+AzvXsJBdvPLcqrxN1RLcBTR\neII+v68uD9dymCtfUWYPkcRsJt9etn4W6NziqX5l4x946iQTyTTvfnnjnMkWTXcqi8gngTRwz2Kf\nG2O+bIzZaYzZ2dtrj3Mlkm+d2aybvMvrobPdXfaq58TZGcanZ+viULYYGggymzE8OzpRl+/fvecY\nfX4vv7ZEtmV/0MfrLg9x374TLdG7drkwGk80TZOGeS2+3C6Dh07GyWRNXRzKFkODQc5MpThZh37k\nxhh27z3GpSE/OzestP37S1GOQBgBCg1Zg/lt5exT9FgR+S/ArwO3mgbWLxiNNfcmh3wrzTI1BMtJ\nVtdVz5yzzH5V+MTZaR55boybr11ftNDYbbs2cG56lgcPnLJ9DEp1ROKJpvkPIGei8fs8ZVc8tbPk\n9VLMBWHUIR9hfzjGwZE4t+1a35QFazkC4TFgs4hsEpF24GbggQX7PADcno822gXEjDGnih0rItcD\nfwi82RgzbdP1lEV0Itk0h7JFJQLhwEiMdreLLaHq+8KWYm3Qx+rO9ro4y77x6HFcItxybXEH2Ssu\nXs2mnk5279HMZacQjSfpa1KEkYUVeloOB8Ix+vzeugqxy9b4aXNLXebK7j3H6Gh385arFrOs15+S\nAiHv+P0Q8BDwDHCfMeaQiLxPRN6X3+1B4ChwBPgK8IFix+aP+QLgB34oIk+JyF32XVbR65kzGTWT\nUMBbthq8/8Q4l68N1LWWiUh9HMvJdIZvPXaCX72sjzXB4lEfLpdw63XreeL4OE+fjNs6DqVyppJp\nJpLpps+V/oCv/LkSHq+ruQjA63FzWX+AAzY3lhqfTvH9/Sd5y1UDtlYjqISynjDGmAeNMVuMMRcb\nY/5Hfttdxpi78q+NMeaD+c+3G2P2FTs2v/0SY8w6Y8yV+b/3nX9m+5lMpplOZRxiMkqWdExls4aD\nIzFbGuKUYvtgN0eik0zZ2CbwXw6OcnYqVXa25duuGcTrcWl9IwcwH3La3LnSF/CWZTKaSOTay9bT\nXGSxPe9YtrNs/D88HiaZznLbdY13Jls03ancaJrVDnAhfQEfqXSW8enZovsdPT3JlM1lfJdix2CQ\nrMk55uxi955jbFjdwSsv6Slr/+6Odn5jx1ruf3KEiUTx/xulvlhBD81KSrMIBXxEJxIlH74HR+IY\nQ12DLyx2DAaZSKQ5dtYea3c2a7hn73GuXt/N1rX25xqVSwsKhOaWrbCY65xWQhW2KitaGZL1xJpI\ndpmNnh2N89iL57j1uvUVFRm7bdcGplMZ7n9yYeyC0kis8gzNKlthEfJ7mc0YzpboQ2CZcBqiTQ/Y\nm93/s+fP8MLpqYbWLVqMFhQIztAQ5sLpSqjCw+EYHe3u85K56kGf38eaoM+28r737DlOu8fF26+p\nLNtyx2CQbQMBdu85rs1zmsh8Rn9zTUbl5u3sD8cY6F7B6gYkc20JdeFrs68f+e49x1jZ0cYbt6+x\n5fuqpeUEwmiTs5Qtym2lORweZ9vaYMPqmdhVzXEqmeZ7T47w69vXVNz/WUS47boNHI5M8NiL52oe\ni1IdkXiSznZ30xycFpaGUsqPcCAcY8e6+msHkMuuv2KtPUEYo7EEP3wmwjt2rsPXZn8lgkpoOYEQ\njSfx+zx0tHuaOo7efHOeSJFwutlMlkMn4w2xiVoMDXbzwukpYjO12e/vf2qEyWSa26rMtnzzlWvx\n+zwagtpEmtkzpJC5bOUii6dzUymOn51uiEPZYvtAkIMj8Zqr9N772HEyWdOwJjjFaDmB4ISQUwBf\nm5uVHW1FfQjPRSZIputTxncprHMdrEFLyDXBOc7WNQGuqtL30dHu4a1XD/KDg6c4PVl5xyyldnKd\n0pqrSQP0WYunIgLBKszYCP+BxY51QWZmMzw/Vn39rXQmy72PnuDVW3rZsNq+7m7V0qICofk3OcyH\nni6FVWK30asemM+OroYnjo/zzKk4t+3aUFO25a3XrWc2Y7hvnzbPaQajDlk8tbld9HS1l5gruft1\nWwMXT5ZjuZa58qNnoozGE9zmAO0AWlIgJJseRmfRVyJbeX84ht/nYePqxrTPg1zY54bVHTXVe9+9\n5xhdXg83Xrm2prFsDvm5btMqvrE3p1IrjSOXwJmci4ZrNn1+X9ES2PvDMS7q6STQQH/HRT2ddHk9\nNc+VNUEfr72sz8aRVU9LCYRs1hCdSBBqYm2WQvpL9FY+MJLLumx0TZPtA8GqoyfOTqX45+FT/ObV\nA3R6a/fT3LZrA+FzM/zbc/ZUuq2E5yITfOfxcEtGOsVmZkmls00PObUIBbxFfQgHwrGGmlYhl1lf\nSz/yF05P8R9HTnPLtevxFKnx1UicMYoGcW46xWzGEPI7x2Q0NpFcdPWbmM3w7KmJhpqLLHYMdjMy\nPlOV7f7b+06QymRti6d+wxX99HR5G+5cPhWb4Y1/8+987Nv7+XoLOradEo1n0R9c2rwajScYjSfY\n3qS58sypCVLpyh3L9+w5hscl3PyyxjbBKUZLCYRRh+QgWPQFfGQNnFnkwfvs6ATprKlrD4SlsFZa\nlarC2azhG48e59qNq2wrxNfucXHzy9bxk8NRwucaUwNxJpXhjrsfp83tYv2qDv7795/mP4+cbsi5\nnYL18HWSyejMVJLZRSJ65pI3mzJXukllshyusGx8YjbDtx8P84Yr+h2jhUGLCQQrjtkpJiNLU1lM\nFbbU0Gaseq4YCCJSubPs34+c5tiZ6fNaZNbKLdetR4BvPlr/5jnGGP7wO8McPBnjb2+5igd/71Vc\n0tvFB+55ghdOt043N6ckcFqEAj6MyfXlXshweByX0JSSD9biabjCQnf/NHyK2Mys7XOlVlpKIDjt\nJp/PwFzsJo/R09XO2iYIry6vh0t6uyrWEHbvOcbqznau39Zv63gGulfw2sv6+NZjJ6pSzSvhS488\nz/f3n+QP3nApv7Y1RJfXw1ffsxOXwO/8/WPEW6S+kuXA7XWIedUqsLeYz214JMaWkL8puUWDK1ew\nsqON4ROVz5WLezt5+UWr6zSy6mgxgZB78PY2uE/pUhTLVh4Oj9etL2w5bB8Msr+CNoEnx2f48TMR\n3vmydXg99mdb3rprA6cnU/zLoVHbv9vih09H+KuHD/PmHWt5/2suntu+blUHd952DcfOTPPhbzzZ\nEhFPo/EE3R1tTc+ctbB6MixcPBljGM73UG4GIsL2we6KtOmDIzGeOjHOrdfVFpZdD1pKIIzGE6zu\nbK9rX4FKWN3Zjks4L5xuKpnmSHSyKQ5lix2D3ZyeTBaN7Cjk3kePY4Bbrq2PCvyazb2sW7Wibs7l\nw6MTfOTeJ9m2Nsin3zZ03kTdddFq/uwt2/jpc2P8xYPP1GUMTsJJIacwv3iKLkjkDJ+b4exUaq7j\nXzPYMRjkF9FJZlLltX69Z+8xfG0u3nrNYJ1HVjnOeDI2iKhDEm0sPG4XPV3nh9MdOhkna2h4GF0h\nVrmM/WWowrOZLN987AS/cmkf61bVJ2fC5RLede0GHn3hLM9F7O37fG4qxe/c/RgdXg9fvv2aJVfF\nt1y7nv/yio189T9e4L7HLuxkuVyWsnPmyurOdjwuOa9zmlV3qxkOZYvtA0EyWcPTp0rPlXhilvuf\nPMmbd6wluKK5NaIWo6UEQq42izPMRRaLhdM1oi9sKbauCeBxSVldoR4+FGFsIsltdXaQvWPnIO1u\nF/fYqCXMZrJ84J4niMST/N27rynZ1e2P33Q5r7ykh0/ef4B9L561bRxOYzSecEx4NuQWBH1+73lz\nZX94nDa3cGl//drLlsIqTV9O7s53Hw8zM5tpepnrpWgpgTAaa34v5YX0+c/PVh4Ox1gb9DXVoedr\nc7Ml5C/rJt+95xgD3St4zZb6Zluu7vJyw/Z+vvvEiG1d3f7sn57m50fP8Bc3befq9StL7u9xu/ji\nu65mcGUHv/v1xxsWCttIMlnD2ESyrn2Jq6Ev3yinkAPhGJevCdTFb1UuoYCPPr+35FwxxrB773F2\nDAabutgrRssIhNlMljNTzhMIoUWylYfD4w2tcLoUO9blMpaLOZaPRCf5+dEzvOu69Q0p0f3uXRuY\nSKZ5YP/Jmr/rnr3HuPvnx7jj1RdVZM8NdrTx1ffsJJXJ8jt/v8/WlqNO4MxkkqxpfmOchYQC3peY\njLJZw4EmOpQLGRrsLpmxvPeFsxyJTnKrQ7UDaCGBcHoyiTHOCTm16A/4ODc9SzKdc0jFpmd58Uxj\ny/guxdBgN7GZWY4XaRN4z95jtLmFdzYo2/KaDSu5rN/P7j3HaiopsefoGf7bPx7iNVt6+aPrL6v4\n+It7u/jCu67mucgEH73vKVt76zab+daZzjEZgVUMcl4gvHhmiolkmh0OmCs7BoMcPT1VtO3r7j3H\nCPg8/MZQbTW+6knLCIT51pnOu8lhPmnOcpI106FsMV/5dHFVeCaV4TuPh7l+2xp6GhTKKyLcumsD\nh07GeepEdTVkTpyd5v27H2f96g4+f8tVVWs2r9nSyx+/aSsPHYrwuR89V9V31Mp0Kr1o9m4tOC2j\n3yIU8BFPpOeieSwTjRO06e2DQYxhyeZSYxNJHjo0ytuuWceKdmeE8i5GywiE+XaAzrrJrXrzlm10\neK4vbPNXPZf2+2n3uOZKCy/k+/tPEk+kG16696arBuhsd1dVY2gqmea9d+8jkzV89fadNUd6/NYv\nbeSdO9fxtz85YosZq1wyWcPf/+xFrvufP+Z1f/1TW4v/Watwp/kQFoaeDodj+NpcbO6rf3vZUlga\n/VLJnPftO8FsxjguM3khLSMQrJvIaQJhrhtULKchDJ+IsWF1B8GO5oektbldbF0TWFJD2L33GFtC\nXVy7aVVDx9Xl9fCWqwb4p+FTnJsq3ni9kGzW8H9/6ymei0zwhXddzUU29KkWEf7sLdu4duMq/uDb\n+21rul6Mx4+d481f+A/+2wOH2LY2iEuE27/2KB+854nzwjKrIRpP4JJcqKeTsLR76xqHw+NcsTbo\niEqhqzrbGVy5YlHHciZr+Mbe47zi4tUN6Y1eC83/n2wQkXgCt0scd5P3L8hWHg6PO8J/YLFjMMih\nkdh52bnD4XGGw7Gam+BUy227NpBKZ/mHx8NlH/O/fvQcDz8d4ZNv2sqrt/TaNpZ2j4s7b7uani4v\n7717X8k+2dVyZjLJH/7Dft565884M5nii++6mm+89zp+8JFX8fuv38KPnonwq599hK/++9GazEiR\neJKeLq8jHrSFzM2ViSTpTJaDJxtf8roYOwa7F61p9MjhKCPjM44NNS3EWb94HRmNJenze3E1qFl9\nuXR3tNHudhGZSDA2keRkLNHQNoCl2D7YzVQqw9GxyZds373nGB3tbm66aqAp47p8TYBrNqzknr3H\nynLo/tPwST7/kyO8/ZpBfvuXNto+ntVdXr76np1MJNLccfc+ErPlZa2WQyZr2L3nGK/97E/57hMj\n/O6rL+LHH3sNbxpag4jg9bj50Gs386OPvobrLlrNn//zM/zG3/4Hj1WZJ+GUTmkL6ZvztyU4MjZJ\nYjbrCIeyxfbBICfO5jKnC9m95xh9fi+v2xpq0sjKp2UEQtQhDcMXIiL0BbxEYom5JDBnrXry1RwL\nVOHY9CwP7D/JjVcO4G9gh6qF3LZrPS+emeY/ny9emvrgSIzf//Z+rtmwkj+/aVvdNJrL1wT4X++8\nkuGRGH/0nWFbGuvsPzHOTV/6T/74/oNcvsbPD37vVXzijZcv2nxo3aoO/vd7dvLld1/DRCLN2+/6\nOX/w7f2LllcvhlP6ji8k4PPga3MRiSfmisk5waFsMVc2vsCxfOLsNI88N8bN166nzWEa12I4f4Q2\n4aReygvpz/dWHg7HEIFtDtIQLurtorPd/RLb+D88ESYxm617ZnIpbti2hpUdbUXrG41NJLnj7n2s\n7GjnrtuuqXsC0+uv6Of3X38p//jUSb70yPNVf8+5qRSf+O4B3vKl/2Q0luBvbr6Sb753F5tL9JkQ\nEV5/RT8//Oiref8vX8z3nhzhtZ/9admaFEB0IunIuSIihAI+RuNJhkfG8Xs9bHJAY3oLKypvuCD6\n7Z69x3GJcMu1zmmCU4wWEgjOS0qzCAV8RCYSDIdjXNLbZUvrSbtwu4QrBoJzjmVjDPfsPcZV67u5\nYm1zBZevzc07XrYu16h8EWdqMp3hfbsf5+x0iq/cvrNhmd8f+OWLefOOtXzmocM8XGF11mzWcO+j\nx3ntZx/hvn0n+O1f2sSPP/YabrxyoCLNpqPdwx9dfxk/+L1XcfkaP5/83kFuuvNnHFwiLNIimc5w\ndirl7LkSz82VbQNBR5mA/b42LurtZDj/f5xMZ7hv3wl+9bK+kiVRnEJLCITEbIbYzKxjb3LLZDQc\njjnKoWyxYzDI06fizGay/Pz5Mxwdm+K265zhILv12g1kjTmveY4xhj/+3kEeP3aOv3r7joZqXSLC\np982xI7BIB/51lM8cype1nEHR2L85p0/4+PfPcDmPj///F9fyZ/8+taazHKbQ36++d5d/M3NVzJy\nbiYXnfSPB4nNLJ5AFXVYp7SFhAI+wmeneeZUnKF1ztGkLXYUZCz/y8FRzk6lloUz2aIlBILTGuMs\nJBTwMZXKcHoy6Sj/gcX2wW5S6VybwN17j9Hd0cabhtY0e1gArF/dwas39/LNR4+/JLLm//vPF/n2\n42H+62sv4debkBnqa3Pz5dt34vd5+J2/31fUjh+bnuVP7j/Ib3zhPwifm+Fz79zBt353F5f129MB\nTES48coBfvyx13D7yzfy9T3H+NXP/pT7nxw5z89hhWf3OdBkBLns6ZOxBLMZ44hcnYVsHwgSiSeJ\nxBPs3nOMDas7eOUlPc0eVtmUJRBE5HoROSwiR0Tk44t8LiLy+fznwyJydaljReTtInJIRLIistOe\ny1kcp2YpWxSuxpwoECzH8o+fifLwoQhvv2bQMY1TIBeCGp1I8qOnIwD823Nj/Pk/P83rt4b4yK9t\nadq4QgEfX373Tk5PJnn/7ifO6/aWzRq+ve8Er/3sI9yz9xjveflGfvyx13DTVYN1cXwHV7TxqTdf\nwQMfeiUDK1fwkW89xS1f2cMvCsqJz88VZy6eCpPlHDlX8lrLt/ed4LEXz3HrdesdZdYqRUmBICJu\n4IvADcBW4BYR2bpgtxuAzfm/O4A7yzj2IPCbwL/VfhnFcWoqvkXhauzyNY3vC1uK9as6CK5o43M/\neo501vAuh5iLLF57WR9rgz527z3G0bFJPvSNJ9gS8vO5d17Z9Mm4Y103n37bEI++eJY/uf/g3Ir8\n6ZNx3vF3P+cP/mGYjT2dfP/Dr+RTb76iITXytw0E+d77X8H/vGk7z5ya4Ia/+Xf+8gfPMp1KOzaj\n36Kw4N7gSufZ5beuCeJ2CX/18HO0e1y8/Zrl4Uy2KMd7eS1wxBhzFEBE7gVuBJ4u2OdG4G6Tu9v3\niEi3iKwBNi51rDHmmfw2u65lSaIOFwiF43LSyttCRNi6JsDPj57hVZt72NTjnMgOyDm+b7l2PZ/9\n4XP86l//lJUd7Xzl9p2Occ7feOUAv4hM8oV/PcL61R2MTSS5++cvsrKjnc+8bYi3Xj3YcMHlcgnv\num49b7gixF/+4Fnu+mmul7TX46Ld7WKlAzLlF8MquOdxiePaTwKsaHcz0L2C42en+fXta1jpsETY\nUpRjMhoACttDhfPbytmnnGPrTiSewNfmIuBzxgNiIZZAaHdwnLK1cn1XnVpk1so782F9xsCXbr26\nbp3bquWjr9vC67eG+MxDh/n7n7/Irddt4Ccf+2XevnNdU7WY1V1ePvP2HXz7fS/H7/Nw9PQUqUzW\nkQ9bgJ68QNhSIvy2mfjacvP4tpc7S5MuB2c+IQsQkTvImaFYv766h9HFvV3cuKOysL1G0uX18IfX\nX8qvXFrfBjO18PEbLuOi3k7HZlv2+X18+q1DrOxsZ9dFq5s9nPNwuYTPvfNK7nzked5wRb+jEqoA\nXrZxFd//8Cv55qPH8Tt04QSwaXUnH/yVi7n5Zc5cmAD89Tuu5CfPRrmqiX2eq0VKZVOKyMuBTxlj\n3pB//wkAY8xfFOzzd8Ajxphv5t8fBn6ZnMmo1LGPAL9vjNlXarA7d+40+/aV3E1RFEUpQEQeN8aU\nDN4px0bxGLBZRDaJSDtwM/DAgn0eAG7PRxvtAmLGmFNlHqsoiqI4gJK6oTEmLSIfAh4C3MDXjDGH\nROR9+c/vAh4E3ggcAaaB3yp2LICI3AT8LdAL/LOIPGVpEoqiKErjKWkychJqMlIURakcO01GiqIo\nSgugAkFRFEUBVCAoiqIoeVQgKIqiKIAKBEVRFCXPsooyEpExYOn2WMXpAYr3Wlw+6LU4jwvlOkCv\nxanUci0bjDG9pXZaVgKhFkRkXzlhV8sBvRbncaFcB+i1OJVGXIuajBRFURRABYKiKIqSp5UEwpeb\nPQAb0WtxHhfKdYBei1Op+7W0jA9BURRFKU4raQiKoihKEVpCIIjI9SJyWESOiMjHmz2exRCRF0Xk\ngIg8JSL78ttWicgPReQX+X9XFuz/ifz1HBaRNxRsvyb/PUdE5PPSgK5AIvI1EYmKyMGCbbaNXUS8\nIvKt/Pa9IrKxwdfyKREZyf82T4nIG51+LSKyTkT+VUSeFpFDIvJ7+e3L7ncpci3L6ncREZ+IPCoi\n+/PX8d/z253zmxhjLug/cmW3nwcuAtqB/cDWZo9rkXG+CPQs2PZp4OP51x8H/t/866356/ACm/LX\n585/9iiwCxDgB8ANDRj7q4GrgYP1GDvwAeCu/OubgW81+Fo+Ra6J08J9HXstwBrg6vxrP/BcfrzL\n7ncpci3L6nfJn7Mr/7oN2Jsfi2N+k7o+KJzwB7wceKjg/SeATzR7XIuM80XOFwiHgTX512uAw4td\nA7l+Ey/P7/NswfZbgL9r0Pg38tKHqG1jt/bJv/aQS86RBl7LUg8ex19LwRj+EXjdcv5dFrmWZfu7\nAB3AE8B1TvpNWsFkNACcKHgfzm9zGgb4kYg8Lrk+0gAhk+s8BzAKWA2Nl7qmgfzrhdubgZ1jnzvG\nGJMGYkCjGyd/WESG8yYlS6VfFteSNxtcRW5Fuqx/lwXXAsvsdxERt4g8BUSBHxpjHPWbtIJAWC68\n0hhzJXAD8EEReXXhhyYn8pdlSNhyHnueO8mZHK8ETgGfbe5wykdEuoDvAB8xxsQLP1tuv8si17Ls\nfhdjTCY/zweBa0Vk24LPm/qbtIJAGAHWFbwfzG9zFMaYkfy/UeB7wLVARETWAOT/jeZ3X+qaRvKv\nF25vBnaOfe4YEfEAQeBM3Ua+AGNMJD+Rs8BXyP02LxlXHkddi4i0kXuA3mOM+W5+87L8XRa7luX6\nu+THPg78K3A9DvpNWkEgPAZsFpFNItJOztHyQJPH9BJEpFNE/NZr4PXAQXLjfE9+t/eQs52S335z\nPqJgE7AZeDSvdsZFZFc+6uD2gmMajZ1jL/yutwE/ya+kGoI1WfPcRO63scblyGvJn/d/A88YY/66\n4KNl97ssdS3L7XcRkV4R6c6/XkHOD/IsTvpN6u0AcsIf8EZykQnPA59s9ngWGd9F5KIJ9gOHrDGS\ns+bV52YAAACtSURBVP39GPgF8CNgVcExn8xfz2EKIomAneQmxvPAF2iMk++b5FT2WXL2zP/LzrED\nPuDbwBFy0RUXNfhavg4cAIbzE26N068FeCU508Mw8FT+743L8Xcpci3L6ncBhoAn8+M9CPxpfrtj\nfhPNVFYURVGA1jAZKYqiKGWgAkFRFEUBVCAoiqIoeVQgKIqiKIAKBEVRFCWPCgRFURQFUIGgKIqi\n5FGBoCiKogDwfwAC8F0kV6KlTAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcef10b9630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(mode='exp_range', gamma=0.99994)\n",
    "\n",
    "model.compile(optimizer=Nadam(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fceed823588>"
      ]
     },
     "execution_count": 237,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=20, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef0dd9710>]"
      ]
     },
     "execution_count": 238,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Ikn4Fx2ZuRJvdpHpBuDKWfIVyPJ01pZj1rMLpWVV6WTnj3V4nDjXY8EhHJYJhge4Jd66X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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fceed9fc240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular._reset(new_base_lr=0.003, new_max_lr=0.009)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fceefb5b400>"
      ]
     },
     "execution_count": 240,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef0e93b38>]"
      ]
     },
     "execution_count": 241,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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HnJocrI5+WbRqNrrYO4Xf5+HAJmVwnMaKINQAvTHP+4xjVsZsOFdEngf6lVKX\nt7nmlHDLaIqzWQ2jtew2HMtO7RIudE/wUF3hPc1BTHHQZiPNdjG/RDhlMoJoGWxgU7NR61CI0rxM\nii34+uykMMdPTWG2dUHomeRQdX7SmvfYgSMrE5Ec4P8EfsfC2BdF5LyInB8dHU3+4gxuDYbwez00\nllpP2V8NPXVAEOaXogkvazsw7a0M4PMI17YZDaHROBlyamJ+/jYzG90emUlZhvJaDlTnWzIZLYcj\nXOkLutqhDNYEoR+oi3leaxyzMmaj481AI3BZRLqM4++ISOXaX66U+qJS6oRS6kRZWZmF5dpD63CI\nprLcbUVXVBdkkeP3OuJYvtQ7xUpEcaLh3v9wWRleWioCXNWRRppt0udAY5y1mIKw0Q5BKUX7yAwt\n5ak1F5kcrM6nc2yW2cXNeyPcHJxmcSXiygqnsVi5250DWkSkUUT8wAvA6TVjTgOfMKKNTgFBpdTg\nRnOVUleVUuVKqQalVANRU9IxpdSQXReWKHeGZ7YdtWBGGjmxQ7jQHXUor1dB8VB1Pte1Y1mzTXon\n5/H7PJQ52MQl2++lpjB7wyJ3Q9MLzCyurJprU83B6gKU2roUtpmQtuN3CEqpFeAzwKvATeCvlVLX\nReQlEXnJGPYK0AG0AV8Cfm2zubZfhc2EFpbpn5qPy0m1uzxvtXNTKjnfPUlLed66NesP1xYwPrvE\nYHAh5evS7Fx6J+aoLcrGk+Ry0lvRWJq7YTtN87PW4pAgHKqx5li+2DNJeSCT6gJ3JqSZ+KwMUkq9\nQvSmH3vs5ZjHCvi01bnrjGmwso5UYXZCiqc3a0t5gL97p5/phWXys9bvwWw3kYjine5JPnikat3z\nZnjctf4g1YXOOQg1O4veyTlH/QcmTWW5fPOdfpRS92Uim5UBnNohVOZnUZzr39KPcLF3iqP1hSnL\npI4X97q7HSSRQlktDkQa3RmZYXphheO7itc9f6AqH4/oSCPN9uidmHc0wsikqTSX0OLKuoUj20ZC\nFOf6HetNLCJbZixPzC7RPT7Hw3XuNheBFoR1aR0KkZ0RtV1ul5aK1AvCecN/cHyDhJdsv5fd5Xlc\n22aafTIJzi3zU3/yBu/0TDq9FM06TC8sE5xfdsUOodEIPV0v0ujO8IxjuwOTA9X53B4OsbQSWff8\n5T6joJ2LM5RNtCCsw+3hEHsq8uKyndYW5eD3eVIqCBe6JynJ9W/a1e2QkbHsFr5zbZArfUH+03du\nOb0UzTpDrj7kAAAgAElEQVT0uiDCyKRpg0gjpRR3RmYc8x+YHKwuYDmsNowuvNIbRCTqy3M7WhDW\nISoI8YWxeT1Cc1ked4ZTF3p6oXuS47uKNrVPHq4pYDS0yMi0OxzLP2iN5pQE55cdXolmPXonoklp\ntUXOm4yqC7Px+zz3RRqNzkRrGDkvCJs7lq/0TdFclkdepiWXraNoQVjD+MwiYzNLCRXKainPS1kZ\n7NHQIt3jc/flH6zFTaWwF5bDvH4nKgi3hkJMOlTqQ7MxfS5ISjPxeoTGktz7dgjmLrwlxSUr1tJY\nkkuO38uNdQRBKcXlvimO7IDdAWhBuA8zwiiRuigt5Xn0Tc5vWn/FLi6s+g/WdyibHKyOOpYv9zkv\nCG91jDO3FOYz794NwJnOCYdXpFlL78QceZk+CnNSEym3FU1l9xe5WxUEh3cIHo+wv2r9jOWB4AJj\nM0s7wn8AWhDuw45WfKZj2WqD8EQ43zWJ3+dZjYfeiBy/j5byAFcMB5eTvHZjmFy/l5d+opmsDA9v\nd4w7vSTNGnon56ktynZNmGRjaS49E3Msh+86bu8MzxDI8lEWcC5xzuRgdT43BqaJrOn/fKU3+nk7\nUqsFYUfSOhyiIDuD8gT+k+1e7Z6WfD/C+e5JHqotINPn3XLskdoCrvQ5m7EciSi+e3OYp/eUkZfp\n48SuYi0ILiTaB8F5c5FJc1keKxF1TzvYOyMhWsrzXCFah6oLmF0K0zV+75fAy31BMryyrarJTqIF\nYQ23h0IJt+LbVZKLzyNJz1heWA5zfSC4pbnI5EhdIROzS46Wwr7aH2R4epH3HagA4FRTsfYjuAyl\nFH0O90FYS/M6+T1tDtYwWsuBDRzLl3un2FeZb+kLmxvQghCD2YpvT4KVEzOMKqnJdixf7p1iOazu\nq3C6EQ8b29YrDvoR/uXmMB6Bd+8tB+BUUwkAZzr1LsEtjM0sMb8cdkVSmonZX7ndiDSamF1ibGZp\n1TzrNGa72lhBiEQU1/qDPFS3MxzKoAXhHoamFwgtrNjSaKOlIvlF7s53R5O6rHZg2lsZwO/1rCbK\nOMFrN4Y50VC82qf6SG0h2Rle3u7QjmW34Iay12vJz8qgIj+T9pGoSabN4ZIVa/H7POypCNzjWO4Y\nmyW0uLJj/AegBeEe7GzFt7s8QPf4LIsr4YRfayPe6Z6kqSzXcmMQv8/D/up8Lvc6IwgDU/PcGgrx\nk/vK71nTiYYi7UdwEW5KSouluSxvdYfglpDTWA5V39uu1gzgeEgLws7kjg0hpyYt5XlEVPIijZRS\nvNMzyfFtltN9qLaAa/1BwpHUO5a/3zoCwHtiBAGiZqNbQyHHWo9q7sX0MbkhKS0WUxCiGcohcvxe\nV1UPPVxbwNTc3Xa1V/qC5BhlY3YKWhBiaB0OURawpxWfadtMlh+he3yOybnlbTfsPlJbyOxSeMP6\n8snk+7dGqC3Kvu8Dcqop6hQ/q/0IrqBvco6SXD+5LsusbS7LJbQQLXLXNhKtYeSGCCOTte1qL/VO\ncaimAK/D5cO3gxaEGG4Ph+Iqeb0eTaV5+DxC61ByCspd7I36D7bbgekhI2My1QlqC8th3mwb5z37\nyu/7EB+uifoR3mrXguAGeifmqXWZuQjuRhq1j8y6oqjdWsx2tVf7gyytRLgxOL36edspaEEwiERU\nQjWM1uL3RSONWoeS8038Ys8UuX7vtsPumsryyPV7U56g9nbHOPPLYd69xlwEsX4E7Vh2A9E+CO4y\nF8FdB/LF3kmGphdcE3JqkpXhZU9FgKv9wdXqpzvJoQxaEFbpnZxjYTlia7PuPZWB1cxnu7nYM8WR\n2sJtb0e9HuFQTUHKHcvfvzVCVoaHx4ww07WcaiqhdTjE+Do1750iElFJDQpwI+GIYmBq3nUOZYg2\no8nxe3n1+jDgfMmK9ThcE/XRXd6BDmXQgrCKnRFGJnsrAvRMzNle02h+KczNwem4G3Y/XFfIzcGN\n67fbjVKK77WO8ERzKVkZ6yfomPkIZ11U1+g//MN1Dv1fr95TLuFBZ2h6geWwclXIqYlItJKw+WXG\nLTkIsRyqLWBybplXrg5SlJPhqlwOK1gSBBF5RkRaRaRNRD67znkRkc8Z56+IyLGt5orI/22MvSQi\n/ywi1fZcUnyY3+TtDGMzxcXujOVrA0FWIiruht1HagtZCke4lST/xlraR2fonZhf11x0d00FRj6C\nO/wISysR/sdb3SyHlatEKtncDTl1542s2UhQ8/s81LpQtEzH8ptt4xypdX/LzLVsKQgi4gU+DzwL\nHAA+JiIH1gx7Fmgxfl4EvmBh7h8opY4opR4G/hH4ncQvJ35ah2eoKcy2tWa5WSCv1Waz0aWexDow\nHUmxY/l7t6LhppsJQoY36kd4yyWC8C83h1cf/9O1IQdXklpMQXDjzRaioacA1QVZroze2RdTFHOn\nOZTB2g7hJNCmlOpQSi0BXwOeXzPmeeArKsrbQKGIVG02VykV+/U0F3Cu4hpwx+iSZif1xTlk+jzc\nHrJXEC72TlJXnB13lcfaomyKc/2rlRiTzfdvjbKvMrBlS9LHmku4PTzDaMh5P8LXzvVSXZDF+w9U\n8Or1ofuqWD6o9E7OIwLVhe6J74/FdCy7UQyAe0yiO82hDNYEoQbojXneZxyzMmbTuSLyH0WkF/g4\nDu4QVsIROkZnbfUfQPQ/bUtFnu07hIs9UxxNoGG3iHCktiAlJSymF5Y51zWx6e7A5MndpQD8uH0s\n2cvalP6peX50Z5SfOVHHc4erGAktcskFZcNTQXBuifysDNcWYzOd3SV5zpe83oj8rKiV4cgOqmFk\n4qhTWSn120qpOuAvgc+sN0ZEXhSR8yJyfnR0NCnr6JmYYykcSUpc854KeyONBoPzDAYXEm64caS2\nkLaRGWYXk9vE5407Y6xE1Goxu804WF1AfpaPN9ucFYRvnI9+h/nZ47W8e185GV7h1TQyG7nZ7H2g\nKp9Pv7uZP/zZh5xeyoZ89cVT/OYH9lIecOcuazOsCEI/UBfzvNY4ZmWMlbkQFYSPrvfLlVJfVEqd\nUEqdKCsrs7Dc7ZPMuih7KwIMTy8yNWdPWQbTfxBvhJHJQ7UFRNTdrMpk8b1bIxRkZ3DMwnq9HuHx\n5lLebBt3rGdDJKL4xvk+ntxdSl1xDgXZGTzeXMo/XR9ytI9EqnD7FXo8wm9+YJ8rw2JNDlYX8Gmj\nG+BOw4ognANaRKRRRPzAC8DpNWNOA58woo1OAUGl1OBmc0WkJWb+88CtBK8lbszyEmYEg53sMZxM\nt22KNLrYO4Xf61mtvx4vR1JQCjsSUfygdYSn95Th81rbjD7RUkr/1Dzd43NbD04Cb3WM0z81z8+e\nuPs95gMHK+ken+OWzb4gt+LiDYImyWz5KVVKrRA157wK3AT+Wil1XUReEpGXjGGvAB1AG/Al4Nc2\nm2vM+T0RuSYiV4D3A//WvsvaHm0jM1QVZBHIsr9/rFkKwy4/wsWeSQ7WJN5woyyQSU1hdlL9CNcG\ngozNLPGefdZ3dk80R/MR3nDIbPQ3F/oIZPl4v9HAB+B9ByoQgVevP/hmozTYBGk2wVKMpVLqFaI3\n/dhjL8c8VsCnrc41jq9rInICs1BWMqgqyCKQ6bMl0mg5HOFqf5CfP7nLhpVFw08vJTHS6PXbUZ/P\nUy3WBaGxNJfqgizebBvjF07Zc51WCS0s851rg3zkWO090SJlgUwe2VXMP10b4t+9d09K1+QEOy12\nXmMfaZ+pHImopAqCiLCnMmDLDqF1KMTCciRh/4HJ0fpC+ibnkxbm+frtMQ7V5FO6jYgQEeGJ3aW8\n1TGe8hLd37k6xMJyhI8eq73v3PsPVnBrKET3eHLKmbsF5XovgiaZpL0gDATnmV8OJ7VQlhlplKhT\n8mJPtMJpohFGJmamczJ2CaGFZd7pmeTpbewOTJ7YXcrU3DI3BlKTSW3yN+/00VSau64D/AMHK4H0\nMBvp/UH6kvaCcCcFrfj2VuQxNbec8Dfxiz1TlOZl2ta45FB1AT6PrAqNnfy4fZyViOLpPdsXhMd3\np96P0DM+x9nOCT56vHZdk0ldcQ6HavJdlbWslOKP/+U2F7rtK62hfQjpTdoLQpsR/ZPMyol7bCph\ncbF3iqP19tVHyfZ72V+Vz8Ue+3cIr98eJdfv5Vgc9ZbKA1nsrQikNB/hb9/pQwQ+fHRtzuVdPnCg\nknd6phieXkjZujbjzbZx/vhf7vALf37W1tfVLoT0RQvCyAylef7Vpu/JYDXSKAHH8uTsEp1js7b5\nD0yO1hdypW/KVnu9UorX74zyWHMpfl98/8Ue313Cua4JFpaTX346ElH87Tt9PNFcSvUm5TWeORQ1\nG/2zC8xGSin+y3dvAzC/HLatUKHeIKQ3aS8Id0ZCqwWzkkVJXialef6EMpbN8FC7/AcmR+ujLTXv\njNgXY981PkfvxDzv2ht/IuGTu0tZXInwTrf95qy1nO2aoG9ynp85fr8zOZbd5Xk0leXyylXnBeGt\n9nHOdU3yG+/dg9/n4a/O9Nj46nqLkK6ktSBEm3XPpKSu+p6KQEI7hCt9QUTulte1C7Mmkp1mIzPc\n9F1xOJRNHm0qweuRlPgR/uZCH3mZvlXH8UaICB86XMWZznFGQs6ajf74u3eoyM/kV97VxAcPV/HN\nd/pt6buhfQjpTVoLwmhokdDCSkpa8UUjjWbirpp5pW+KptJc25PndpXkUJSTYatj+Ye3R2koyaG+\nJP7yAnmZPh6uK+TNJPdZnl1c4ZWrg3zwcBXZ/q2T/T54pJqIwtHaRmc6xjnbOcFL72omK8PLxx+t\nJ7S4wj9cHrDl9bUPIX1Ja0FIRYSRyd7KAPPLYfom57c9VynF5b5gUtrxiQhH64ts2yEsroR5q308\nruiitTyxu5SrfVME55ZtWNn6vHp9iLmlMB/dwlxksqcij93lefzjlcGkrWkrPv+Ddkrz/HzsZD0A\nx3cVsbciwF/aYjbSW4R0Jq0FYbWoXQoEYU8CJSyGphcYDS2uNraxm6N1hdwZmSE4n/iN90LXJPPL\n4bjyD9by5O5SIoqkNs355sV+6oqzeaTBWjSUiPChI1Wc7ZpgxIFoo6t9QV6/PcovPdm0mk0tIvz8\no/Vc6QtyxYZSJHqDkL6ktSDcGQmRn+WLu9HMdjCb78TjWL7cGy1Ad8Rmh7KJmaBmx83kh3dGyfAK\njxk1iRLh4bpCcvxe3mhLTtnz0dAib7aN8fxDNdsK5f3g4SqUgu84YDb6wg/bCGT5+IVT9fcc//Cx\nGrIzvAk7l7UPIb1Jb0EYjpasSEXtlkBWBjWF2XFVzLzSN4XPIxyoSqzC6UYcqStAxB7H8uu3xzi+\nq4hcG1qR+n0eHm8u4fXbyXEs/+OVASIKnn94e+28WyoC7K0I8O0Um43aRmb4zrUhPvlYw32+pPys\nDH7qoWq+dWmA6YXkmdg0DzZpLQjtozMpcSib7K0M0BpHvPiVviB7KgL3FFyzk/ysDFrK8xJ2LI+E\nFrg5OG2L/8Dk6T1l9EzM0TVmfw2hb10aYH9Vflx9MD54pIpz3RMMBVNnNnr5h+1k+jx86omGdc9/\n/FQ988th/v7iei1HrKGUdiqnM2krCJOzS4zNLKXEoWyyvypA++gsiyvWk62UUlzpm+KhJLfjO1pX\nxMXeqYTqLf3I+CZvh//AxHytH96212zUNTbLpd4pfnqbuwOT51bNRqnZJfRPzfP3F/t54ZH6DdtH\nHqkt5HBNAX91pictmvlo7CdtBaFt1IgwSkEOgsm+ynzCRnVVq3SNzzG9sJL0ht1H6wuZmlumK4HG\nNG+0jVGS67fVtNVQmkt9cc5qboNdnL48gAj8q4fiE4Td5Xnsq0yd2ehLr3cA8OLTTZuO+/ij9dwa\nCnE+zoQ+hUK0WzltSVtBuJOCGkZr2V8VNU3cHLTuRzAdvcmKMDIxHcvxmo2UUrzZNsbju0vxeOy9\nobxrTxlvdYyztBKx5fWUUvz9pX5ONhRvWqpiKz50pIrz3ZMMBrcfSrwdxmYW+erZHj5yrGbL9f7U\nw9XkZ/n47z/uSuqaNA8m6SsIIyGyM7xUF9hTOdQKDSW5ZPo83Bq07ke43Bsk0+dZDVtNFrvL88jL\n9MXtWG4bmWEktMiTuxOPLlrL03vKmFsKc96mqp7XB6bpGJ3l+Yc3LmRnhecOVwEkvZTFf3uzk6Vw\nhJfe1bzl2By/j597pI5/ujYUl1BpH0J6k7aCYDbFsfvb7Gb4vNEb+3Yija70TXGwOp8Miz2J48Xr\nER6qK+Bib3w7BLMy6ePNpXYuC4DHmkvwecS2aKNvXeonwys8d3jzUhVb0VSWx4GqfL59xZ4M4fWY\nXVzhf77VzTMHK2myWHPrE481EFGKv3zbzvpGmnTA0l1GRJ4RkVYRaRORz65zXkTkc8b5KyJybKu5\nIvIHInLLGP9NEUmukXwNbSMzKTUXmeyvCliuTLkSjnBtIJh0/4HJ0boibg6GmF/afoXRN9vHqS/O\noa44/nIVG5GX6eP4riJbHMvhiOL05QHetaecwpzEK9x+8EgV7/RM0TcZv+9lM75xvpfphRV+eQvf\nQSx1xTn85L4Kvnq2Z9vVYhU6MS2d2VIQRMQLfB54FjgAfExEDqwZ9izQYvy8CHzBwtzXgENKqSPA\nbeC3Er4ai4QWlhkMLtDsgCDsq8xnbGbJUnG0OyMzLCxHkh5hZHK0vpBwRG07QW0lHOHt9nGe2G3/\n7sDk6T1l3BycTrio3JnOcYanF/npo/E5k9fyr45EX+cfLtvvXA5HFH/xZifHdxVtu6/Ep55oYHx2\nydESG5qdh5UdwkmgTSnVoZRaAr4GPL9mzPPAV1SUt4FCEanabK5S6p+VUmZ5xrcBa8VkbKB9NBrT\nnsqQU5N9hmP5lgXH8l2Hcop2CMZN58I2HctX+4OEFld4Ign+A5N3GbkNP0rQbPStiwPk+r385L4K\nO5ZFfUkOx+oL+dal+GP/N+LV60P0Tszzy081bnvu480ltJTn8T9+3LWtENSoD0HvEdIVK4JQA/TG\nPO8zjlkZY2UuwL8BvmNhLbbQYYScJrsPwnrsr4yGZFoxG13pCxLI9NFYkpvsZQFQnOunqTSXC13b\nE4QfGxVJH2tKniAcqMqnNM/P63fiNxstrUT4zrVB3n+w0lJlU6v89NEabg2FbGtSY/KlH3WwqySH\n9x3Yvq9DRPjk4w1c7Q/yThJapGoeTBx3KovIbwMrwF9ucP5FETkvIudHR+2JRW8fncHnEXYlUJ45\nXopy/VTmZ1kKPb3SF+RwbUFKHd/HdxVxoWdyW2W637gzxv6q/A0TpuzA4xGeainjR3fG4i4h/mbb\nGNMLK/yrh6psXdtzh6vweoRvXbLPuXyhe4KLPVP8myca8cb5/n/4aA2BLB//7c0u29alebCxIgj9\nQF3M81rjmJUxm84VkV8EPgR8XG2wr1VKfVEpdUIpdaKszJ4M2I7RWeqLc5IeubMR+6oC3Nwi9HRx\nJdoWMVXmIpMTDUVMzS3TMWYteW5hOcyFnsmkhJuu5ek9pUzMLnFtIBjX/H+8Mkggy8eTu+3LpAYo\nzcvkqZZSTl8aiFus1vKl1zspyM7gZ0/Eb0nNzfTxcyeiIahWS2woXf46rbFyRzwHtIhIo4j4gReA\n02vGnAY+YUQbnQKCSqnBzeaKyDPAvwd+SimVnBCNDWgfnbEcwpcM9lfl0z46s2mi1c3BEMthxUNJ\nTkhby/FdxQCct2g2Ot81ydJKhMeT6FA2ecooYxFP1vLSSoR/vjHE+w9Uxt3neTOef7ia/qn5bftf\n1qN7fJZXbwzx8UfryfEnViTwE481EFaKvzzTbXmOdiGkL1t+MgzH72eAV4GbwF8rpa6LyEsi8pIx\n7BWgA2gDvgT82mZzjTl/AgSA10Tkkoi8bN9lbUw4ougam6O5LDV2+fXYVxlgOaxoH934W/iqQzlJ\nJa83orksl6KcDMulD95oG8PnEU42FCd5ZdFv4odq8uPKR3ijbZTQwgofOmKvucjk/Qcqyc7wJlRY\nzuQv3ujE5xF+8fGGhF+rviSHn9xXzl+dsRiCqjcIaY2lr0pKqVeUUnuUUs1Kqf9oHHtZKfWy8Vgp\npT5tnD+slDq/2Vzj+G6lVJ1S6mHj56X7f7P99E3OsRSOOOJQNjFr/WzmhLzSF6Qk1091QVaqlgVE\nnZHHdxVxwaIg/Lh9jGP19pS7tsLTLWVc6Jncdonnb18ZIj/Ll7TQ2NxMH+87UMG3rw4mVGJjam6J\nb5zv4/mHayjPt+e9/6UnmxifXeLv3rEmVnqHkL447lRONR1GyGmTgzuExtJc/F7PpqGn1/qDHKop\ncCQE8PiuYjrHZhmbWdx0XHBumav9QR5Pgf/A5N37yglH1LbCTxdXwlFz0cHkmItMnn+4mqm5ZX6U\nQCTU18/1Mr8c5pee3H6o6UacairmUE0+f/5Gx5Y+Dr1BSG/SThDaHQw5NfF5PbRU5HFjA8fywnKY\nOyMzHKpJTkOcrThhtJPcapfwVscYSpHUhLS1HK0rpCA7g+/dGrE85407Y4QWVvhgksxFJk/vKaMo\nJ4O/jzPaKBxR/M+3u3m0sZj9NlaMFRF++akmOkZnLf3ddLXT9CUNBWGWopwMinITL1uQCPur8jes\nadQ6FCIcURyqTq1D2eRwTQF+r4d3thCEN9vGyfV7eTiFfg6f18NP7C3jh7dHLEf0fPvqYNRclIQ6\nS7FkeD08d7iK124MMbO4svWENXz35jB9k/O2+A7W8tzhKqoLsvjSjzo2Haf7KKQ3aSgIM47uDkz2\nVQYYDS2ua5a52h8NqzxU44wgZGV4OVSTv6Vj+c32MU42Fqc8fPc9+8oZm1niSv/W4aeLK2Feuz7M\nB5JsLjL56aM1LCxHeO3G9iug/o+3uqguyOJ9B+zJoo4lw+vh3zzZyJnOiS1Lk2gfQvqSdoLQMTrr\nqP/AxDQJrOdHuD4QpCA7g9qi1JXmXsuJhmKu9gU3jEwZnl6gY3Q2KdVNt+Jde8rwCJbMHz+6PUZo\ncYXnkmwuMjleX0RNYTbfvLg9s9Gd4RBvto3z8VO78CVJYH/ukToCmT6+9KPODcfo/UF6k1aCEJxf\nZmxm0TU7BFg/0uha/zSHavIdrSlzfFcRS+EI1zb4Fv52R7RcxakklqvYiMIcP8fqi/jereEtx75y\ndZCC7Iykm4tMPB7hI8dqeOPO6Lb6Lf/3H3fh93n42Mn6pK0tkJXBxx6t55Wrg0mrzqrZ2aSVIJg1\njJxMSjMpycukPJB5XwmLpZUIrUMhx/wHJsd3RR3LG5mN3u6YIJDp40C1M47vd+8r51r/NCPTG990\nF1fCvHZjmA8crEiJucjkI8dqiSj4psWchOD8Mn/3Tj8/9VA1xUn2bf3i4w0IbFjOQild/jqdSStB\naHdByGks+6vy7ythcXs4xFI44pj/wKQ0L5PG0twNM5bPdIxzsrE47jo7ifKefeUAfL91Y7PRqrno\ncGrMRSaNpbmc2FXE31zoteSk/cb5aKhpMpzJa6kuzOZDR6r42tkegvPby+XQPPiklSB0GEXt6pPQ\nxCUe9lUFaBuZYTl8N5Hp+oCzDuVYju8q4p2eyftuasPTC3SMzTpiLjLZVxmgqiBrUz/CP10fIpDl\nc8TP8TPHa2kfneVy3+aO74gRanp8V1HK3vP/9akmZpfC/NWZ+zuqKXT563QmrQShfXSG+hLnitqt\n5UBVPkvhyD0lLK71T5OX6WOXC0TrxK4iJmaX6Bibvee4k/4DExHh3fvKeePOGIsr9zu+V8IRvntz\nmJ/cV55Sc5HJc0eqyPR5+JsLvZuO+8HtEbrH5/hkCnYHJodqCniqpZS/eKNz2x3VNA827rgzpoiO\n0VlXOJRNzBIWsWajawNBDlTnp7Tk9UasJqitMRud6XTWf2Dynr3lzC6FOdd5v1nrbNcEk3PLPHMo\nsb7J8ZKflcEzhyr5h8uDm950v/JWN+WBTJ5N8Tp/9SeaGZtZ5BsX+u45rpTSPoQ0Jm0EYSUcoWvc\nHSGnJo2luWT6PNwYiArCSjjCzcFpDrvAXATQVJpHYU4G57sn7jn+dsc4jzjoPzB5fHcJfp9nXbPR\nP18fJtPn4ek99pa63g4fPVZLcH6Z795c36zVOzHHD2+P8sLJ+pTvWh9rKuFofSF/9sP2e0yWmvQm\nbQShb3Ke5bBy1Q7B5/WwrzLAdUMQ2kdnWViOOFayYi0ej3C8vugex/KIkX9wqin51U23Isfv47Gm\nkvscy0opXr0+xNN7yhIuH50IT+wupTI/a0Oz0dfO9SDAC4/UrXs+mYgIn/6J3fRNzvMPl+/mTCjQ\nYUZpTNoIwt0aRu7ZIQAcqM7nxuA0SqnVmH+nQ05jOdlYTMfYLKOhaEb1253R3YKT/oNY3rOvnM6x\nWTpj/BxX+oIMBhf4wEFnzEUmXiMn4fU7Y/eFxy6HI3z9XB/v3ltOdaEzCYjv2VfOvsoAf/qDdtsa\n+2h2NmkjCKtVTkvds0OAqB9ham6ZweAC1waCZGV4XJEnYfJIY3QncK4rKgRvd4xH/Qc2Fl9LBDP8\n9Ls37yapvXp9CK9HeO/+cqeWtcpHj9cSjij+/tK9OQmv3RhmbGaRj59KXiLaVng8wq/+RDNtIzO8\nZv79dB5CWpM2gtA+OkNxrt/xonZrOWDsBq4PTHO9f5oDVfmO2+ZjOVRdQFaGh7OddwXhkcbipJVX\n2C51xTnsqci7x07/6vUhTjUVU5jj/HvdXJbH0fpC/vZC/z3hu391poeawmzetcdZ0frg4Srqi3P4\n0++36cJ2mvQRhGiEkbvMRRCNpxeJ9j+4PhB0jUPZxO/zcLSuiHNdE67yH8Ty3v0VnO2aIDi3TNtI\niPbRWcfNRbH8zPFaWodDq0ULu8ZmeaNtjJ97pM5x8fd5Pbz0rmYu9wV5s20chdJ5CGlM2ghC++iM\n68xFEO201ViSyytXB5ldCnPQZYIAUT/CjcHpVbOCW/wHJu89UEE4ovjB7RFevR5d4/sPuEcQPnSk\nmlRiZeoAAAd+SURBVEyfh6+fizqXv3quB69H+DkHnMnr8dHjNZQHMvn899ucXorGYSwJgog8IyKt\nItImIp9d57yIyOeM81dE5NhWc0XkZ0XkuohEROSEPZezPlNzS4zPLtFc7r4dAsD+6nzujESd3m5y\nKJucbCxGKfjT77eT5yL/gcnDtYWU5vl57cYwr14f4qG6QipT3Hp0MwqyM3jucBWnLw0QnF/mG+f7\neO/+cipsapGZKJk+Ly8+3cRbHeNc7g1qH0Ias6UgiIgX+DzwLHAA+JiIHFgz7Fmgxfh5EfiChbnX\ngI8Aryd+GZvT7lKHsknsDbalwn1rPFpfiM8j9E/N80hDkWv8ByYej/CT+yr4xyuDXOkL8oGD9vcT\nSJR/faKO0OIKv/H1S0zMLvHzj+5yekn38POP1lOc66d/at7ppWgcxMon+yTQppTqUEotAV8Dnl8z\n5nngKyrK20ChiFRtNlcpdVMp1WrblWyCWeW0udx9N1vgnoxft5TViCXH71v9Nus2c5HJe2Oayjzj\nIv+ByammYhpKcvjerRHqirN5KoVtR62Q4/fxy081AbpBTjpj5e5TA8Rm1vQZx6yMsTI36bSPzpLh\nFeocbDizGQcNQUh26eNEME0wZhiq23gy5gbrprBdExFZrbr6Uw9Vu6I0yVo+8dguinIynF6GxkGc\nS+O0iIi8SNQMRX19fDHbDSU5fPhojetMHSblgSx+8wN7efde5+PmN+KP/vVDfP1cLw/Vpq5/8nbI\n9nv5vY8cdo1dfj1+5elm5pfDvPhUs9NLWZfcTB9/8DMP6bLYaYxsFXssIo8Bv6uU+oDx/LcAlFL/\nb8yYPwN+oJT6qvG8FfgJoMHC3B8A/4dS6vxWiz1x4oQ6f37LYRqNRqOJQUQuKKW2DN6x8pX5HNAi\nIo0i4gdeAE6vGXMa+IQRbXQKCCqlBi3O1Wg0Go0L2NJkpJRaEZHPAK8CXuDLSqnrIvKScf5l4BXg\nOaANmAM+tdlcABH5MPBfgTLg2yJyydxJaDQajSb1bGkychPaZKTRaDTbx06TkUaj0WjSAC0IGo1G\nowG0IGg0Go3GQAuCRqPRaAAtCBqNRqMx2FFRRiIyCnTHOb0UGLNxOU6ir8V9PCjXAfpa3Eoi17JL\nKVW21aAdJQiJICLnrYRd7QT0tbiPB+U6QF+LW0nFtWiTkUaj0WgALQgajUajMUgnQfii0wuwEX0t\n7uNBuQ7Q1+JWkn4taeND0Gg0Gs3mpNMOQaPRaDSbkBaCICLPiEiriLSJyGedXs96iEiXiFwVkUsi\nct44Viwir4nIHePfopjxv2VcT6uIfCDm+HHjddpE5HMiyW+IKCJfFpEREbkWc8y2tYtIpoh83Th+\nRkQaUnwtvysi/cZ7c0lEnnP7tYhInYh8X0RuiMh1Efm3xvEd975sci076n0RkSwROSsil43r+A/G\ncfe8J0qpB/qHaNntdqAJ8AOXgQNOr2uddXYBpWuO/T7wWePxZ4H/ZDw+YFxHJtBoXJ/XOHcWOAUI\n8B3g2RSs/WngGHAtGWsHfg142Xj8AvD1FF/L7xJt4rR2rGuvBagCjhmPA8BtY7077n3Z5Fp21Pti\n/M4843EGcMZYi2vek6TeKNzwAzwGvBrz/LeA33J6Xeuss4v7BaEVqDIeVwGt610D0X4TjxljbsUc\n/xjwZylafwP33kRtW7s5xnjsI5qcIym8lo1uPK6/lpg1fAt4305+X9a5lh37vgA5wDvAo256T9LB\nZFQD9MY87zOOuQ0F/IuIXJBoH2mAChXtPAcwBFQYjze6phrj8drjTmDn2lfnKKVWgCBQkpxlb8iv\ni8gVw6Rkbul3xLUYZoOjRL+R7uj3Zc21wA57X0TEKyKXgBHgNaWUq96TdBCEncKTSqmHgWeBT4vI\n07EnVVTyd2RI2E5eu8EXiJocHwYGgT90djnWEZE84G+Bf6eUmo49t9Pel3WuZce9L0qpsPE5rwVO\nisihNecdfU/SQRD6gbqY57XGMVehlOo3/h0BvgmcBIZFpArA+HfEGL7RNfUbj9cedwI71746R0R8\nQAEwnrSVr0EpNWx8kCPAl4i+N/esy8BV1yIiGURvoH+plPo74/COfF/Wu5ad+r4Ya58Cvg88g4ve\nk3QQhHNAi4g0ioifqKPltMNrugcRyRWRgPkYeD9wjeg6P2kM+yRR2ynG8ReMiIJGoAU4a2w7p0Xk\nlBF18ImYOanGzrXHvtbPAN8zvkmlBPPDavBhou+NuS5XXovxe/8CuKmU+qOYUzvufdnoWnba+yIi\nZSJSaDzOJuoHuYWb3pNkO4Dc8AM8RzQyoR34bafXs876mohGE1wGrptrJGr7+y5wB/gXoDhmzm8b\n19NKTCQRcILoB6Md+BNS4+T7KtEt+zJRe+Yv2bl2IAv4BtBGNLqiKcXX8j+Bq8AV4wNX5fZrAZ4k\nanq4Alwyfp7bie/LJteyo94X4Ahw0VjvNeB3jOOueU90prJGo9FogPQwGWk0Go3GAloQNBqNRgNo\nQdBoNBqNgRYEjUaj0QBaEDQajUZjoAVBo9FoNIAWBI1Go9EYaEHQaDQaDQD/P5L+hCgjgkoDAAAA\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fceefc41a20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr = lambda x: 0.5*(1+np.sin(x*np.pi/2.))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(scale_fn=clr, scale_mode='cycle')\n",
    "\n",
    "model.compile(optimizer=Nadam(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcefa47f2b0>"
      ]
     },
     "execution_count": 244,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=40, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcefa228588>]"
      ]
     },
     "execution_count": 245,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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dsw59Hy4y1RNDCC9wx6J2bpM7FrlL4krQU423UupJGIO+/bVHbT8rAO/1eq75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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcefa47f908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr = lambda x: 1/(5**(x*0.0001))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clr_triangular = CyclicLR(scale_fn=clr, scale_mode='iterations')\n",
    "\n",
    "model.compile(optimizer=Nadam(), loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fcefa47a160>"
      ]
     },
     "execution_count": 248,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X, Y, batch_size=2000, nb_epoch=10, callbacks=[clr_triangular], verbose=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcef281f0b8>]"
      ]
     },
     "execution_count": 249,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+0f20O6+Sp/ec5EuXJDIjNtTucHr0rU9PoaGljb++n2t3KMpmmiguQE19M4eK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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fcefa472940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(clr_triangular.history['iterations'], clr_triangular.history['lr'])\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
